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Wiring and Molecular Features of Prefrontal Ensembles Representing Distinct Experiences
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SUMMARY A major challenge in understanding the cellular diversity of the brain has been linking activity during behavior with standard cellular typology. For example, it has not been possible to determine whether principal neurons in prefrontal cortex active during distinct experiences represent separable cell types, and it is not known whether these differentially active cells exert distinct causal influences on behavior. Here, we develop quantitative hydrogel-based technologies to connect activity in cells reporting on behavioral experience with measures for both brain-wide wiring and molecular phenotype. We find that positive and negative-valence experiences in prefrontal cortex are represented by cell populations that differ in their causal impact on behavior, long-range wiring, and gene expression profiles, with the major discriminant being expression of the adaptation-linked gene NPAS4. These findings illuminate cellular logic of prefrontal cortex information processing and natural adaptive behavior and may point the way to cell-type-specific understanding and treatment of disease-associated states.
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Cites
Nothing in Biology Makes Sense except in the Light of Evolution
Dobzhansky, T. (1973) · The American Biology Teacher · doi:10.2307/4444260 · Cited by 3,219
A mesoscale connectome of the mouse brain
Oh, S. W., Harris, J. A., Ng, L., Winslow, B., Cain, N., Mihalas, S., Wang, Q., Lau, C., Kuan, L., Henry, A. M., et al. (2014) · Nature · doi:10.1038/nature13186 · Cited by 2,612
Self-citationStructural 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
Self-citationContext and Behavioral Processes in Extinction: Table 1.
Bouton, M. E. (2004) · Learning & Memory · doi:10.1101/lm.78804 · Cited by 1,808
Prefrontal executive and cognitive functions in rodents: neural and neurochemical substrates
Dalley, J. W., Cardinal, R. N., & Robbins, T. W. (2004) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2004.09.006 · Cited by 1,329
Input-specific control of reward and aversion in the ventral tegmental area
Lammel, S., Lim, B. K., Ran, C., Huang, K. W., Betley, M. J., Tye, K. M., Deisseroth, K., & Malenka, R. C. (2012) · Nature · doi:10.1038/nature11527 · Cited by 1,300
Self-citationCortical interneurons that specialize in disinhibitory control
Pi, H.-J., Hangya, B., Kvitsiani, D., Sanders, J. I., Huang, Z. J., & Kepecs, A. (2013) · Nature · doi:10.1038/nature12676 · Cited by 1,136
A translational profiling approach for the molecular characterization of CNS cell types
Heiman, M., Schaefer, A., Gong, S., Peterson, J. D., Day, M., Ramsey, K. E., Suárez-Fariñas, M., Schwarz, C., Stephan, D. A., Surmeier, D. J., et al. (2008) · Cell · doi:10.1016/j.cell.2008.10.028 · Cited by 1,134
Intact-brain analyses reveal distinct information carried by SNc dopamine subcircuits
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., et al. (2015) · Cell · doi:10.1016/j.cell.2015.07.014 · Cited by 794 · cited 2×
“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…”
Projection-specific modulation of dopamine neuron synapses by aversive and rewarding stimuli
Lammel, S., Ion, D. I., Roeper, J., & Malenka, R. C. (2011) · Neuron · doi:10.1016/j.neuron.2011.03.025 · Cited by 766
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Three-dimensional intact-tissue sequencing of single-cell transcriptional states
Wang, X., Allen, W. E., Wright, M. A., Sylwestrak, E. L., Samusik, N., Vesuna, S., Evans, K., Liu, C., Ramakrishnan, C., Liu, J., et al. (2018) · Science · doi:10.1126/science.aat5691 · Cited by 1,620
Self-citationEngrams and circuits crucial for systems consolidation of a memory
Kitamura, T., Ogawa, S. K., Roy, D. S., Okuyama, T., Morrissey, M. D., Smith, L. M., Redondo, R. L., & Tonegawa, S. (2017) · Science · doi:10.1126/science.aam6808 · Cited by 1,104
Activity-Regulated Transcription: Bridging the Gap between Neural Activity and Behavior
Yap, E.-L., & Greenberg, M. E. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.013 · Cited by 706
Astrocytic Activation Generates De Novo Neuronal Potentiation and Memory Enhancement
Adamsky, A., Kol, A., Kreisel, T., Doron, A., Ozeri-Engelhard, N., Melcer, T., Refaeli, R., Horn, H., Regev, L., Groysman, M., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.002 · Cited by 631
Integration of optogenetics with complementary methodologies in systems neuroscience
Kim, C. K., Adhikari, A., & Deisseroth, K. (2017) · Nature reviews. Neuroscience · doi:10.1038/nrn.2017.15 · Cited by 690
Self-citationThirst-associated preoptic neurons encode an aversive motivational drive.
Allen, W. E., DeNardo, L. A., Chen, M. Z., Liu, C. D., Loh, K. M., Fenno, L. E., Ramakrishnan, C., Deisseroth, K., & Luo, L. (2017) · Science · doi:10.1126/science.aan6747 · Cited by 390
Protection of tissue physicochemical properties using polyfunctional crosslinkers
Park, Y.-G., Sohn, C. H., Chen, R., McCue, M., Yun, D. H., Drummond, G. T., Ku, T., Evans, N. B., Oak, H. C., Trieu, W., et al. (2019) · Nature Biotechnology · doi:10.1038/nbt.4281 · Cited by 421
Prefrontal cortex output circuits guide reward seeking through divergent cue encoding
Otis, J. M., Namboodiri, V. M. K., Matan, A. M., Voets, E. S., Mohorn, E. P., Kosyk, O., McHenry, J. A., Robinson, J. E., Resendez, S. L., Rossi, M. A., et al. (2017) · Nature · doi:10.1038/nature21376 · Cited by 412
The hippocampus and related neocortical structures in memory transformation
Sekeres, M. J., Winocur, G., & Moscovitch, M. (2018) · Neuroscience Letters · doi:10.1016/j.neulet.2018.05.006 · Cited by 370
Cardiogenic control of affective behavioural state
Hsueh, B., Chen, R., Jo, Y., Tang, D., Raffiee, M., Kim, Y. S., Inoue, M., Randles, S., Ramakrishnan, C., Patel, S., et al. (2023) · Nature · doi:10.1038/s41586-023-05748-8 · Cited by 335
Self-citationCombined Social and Spatial Coding in a Descending Projection from the Prefrontal Cortex
Murugan, M., Jang, H. J., Park, M., Miller, E. M., Cox, J., Taliaferro, J. P., Parker, N. F., Bhave, V., Hur, H., Liang, Y., et al. (2017) · Cell · doi:10.1016/j.cell.2017.11.002 · Cited by 311
Self-citationEncoding of contextual fear memory in hippocampal–amygdala circuit
Kim, W. B., & Cho, J.-H. (2020) · Nature Communications · doi:10.1038/s41467-020-15121-2 · Cited by 289
Lateral habenula in the pathophysiology of depression
Yang, Y., Wang, H., Hu, J., & Hu, H. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.10.024 · Cited by 254
Ancestral Circuits for the Coordinated Modulation of Brain State
Lovett-Barron, M., Andalman, A. S., Allen, W. E., Vesuna, S., Kauvar, I., Burns, V. M., & Deisseroth, K. (2017) · Cell · doi:10.1016/j.cell.2017.10.021 · Cited by 212
Self-citationThe role of population structure in computations through neural dynamics
Dubreuil, A., Valente, A., Beiran, M., Mastrogiuseppe, F., & Ostojic, S. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01088-4 · Cited by 237
Fear extinction requires infralimbic cortex projections to the basolateral amygdala
Bloodgood, D. W., Sugam, J. A., Holmes, A., & Kash, T. L. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0106-x · Cited by 229
An interactive framework for whole-brain maps at cellular resolution
Fürth, D., Vaissière, T., Tzortzi, O., Xuan, Y., Märtin, A., Lazaridis, I., Spigolon, G., Fisone, G., Tomer, R., Deisseroth, K., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-017-0027-7 · Cited by 215
Self-citationThe mouse prefrontal cortex: Unity in diversity
Le Merre, P., Ährlund-Richter, S., & Carlén, M. (2021) · Neuron · doi:10.1016/j.neuron.2021.03.035 · Cited by 207
Chang, E. H., Argyelan, M., Aggarwal, M., Chandon, T.-S. S., Karlsgodt, K. H., Mori, S., & Malhotra, A. K. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.068 · Cited by 186
A labeled-line neural circuit for pheromone-mediated sexual behaviors in mice
Ishii, K. K., Osakada, T., Mori, H., Miyasaka, N., Yoshihara, Y., Miyamichi, K., & Touhara, K. (2017) · Neuron · doi:10.1016/j.neuron.2017.05.038 · Cited by 185
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
Kim, C. K., Ye, L., Jennings, J. H., Pichamoorthy, N., Tang, D. D., Yoo, A.-C. W., Ramakrishnan, C., & Deisseroth, K. (2017) · Cell · doi:10.1016/j.cell.2017.07.020 · Cited by 145
Self-citationNectow, A. R., & Nestler, E. J. (2020) · Nature reviews. Neuroscience · doi:10.1038/s41583-020-00382-z · Cited by 159
Concepts, goals and the control of survival-related behaviors
Feldman Barrett, L., & Finlay, B. L. (2018) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.10.001 · Cited by 89
AxTract: Toward microstructure informed tractography
Girard, G., Daducci, A., Petit, L., Thiran, J., Whittingstall, K., Deriche, R., Wassermann, D., & Descoteaux, M. (2017) · Human Brain Mapping · doi:10.1002/hbm.23741 · Cited by 62
Prefrontal feature representations drive memory recall
Yadav, N., Noble, C., Niemeyer, J. E., Terceros, A., Victor, J., Liston, C., & Rajasethupathy, P. (2022) · Nature · doi:10.1038/s41586-022-04936-2 · Cited by 61
Selective filtering of excitatory inputs to nucleus accumbens by dopamine and serotonin
Christoffel, D. J., Walsh, J. J., Hoerbelt, P., Heifets, B. D., Llorach, P., Lopez, R. C., Ramakrishnan, C., Deisseroth, K., & Malenka, R. C. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2106648118 · Cited by 54
Self-citationPastor, V., & Medina, J. H. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15168 · Cited by 50
Laque, A., L. De Ness, G., Wagner, G. E., Nedelescu, H., Carroll, A., Watry, D., M. Kerr, T., Koya, E., Hope, B. T., Weiss, F., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11799-1 · Cited by 43
Selective engram coreactivation in idling brain inspires implicit learning
Aly, M. H., Abdou, K., Okubo-Suzuki, R., Nomoto, M., & Inokuchi, K. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2201578119 · Cited by 39
Blacktop, J. M., & Sorg, B. A. (2019) · Neuropsychopharmacology · doi:10.1038/s41386-018-0212-8 · Cited by 40
Metadata
- Authors
- Ye, L., Allen, W. E., Thompson, K. R., Tian, Q., Hsueh, B., Ramakrishnan, C., Wang, A.-C., Jennings, J. H., Adhikari, A., Halpern, C. H., Witten, I. B., Barth, A. L., Luo, L., McNab, J. A., & Deisseroth, K.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2016-06
- Volume
- 165
- Issue
- 7
- Pages
- 1776-1788
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2402763080
- Cited by
- 328
- References
- 20
- FWCI
- 21.50
- Type
- journal article
- Language
- en
- Open access
- bronze
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