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Patel RR, Patarino M, Kim K, Pamintuan R, Taschbach FH, Li H, Lee CR, van Hoek A, Castro R, Cazares C, Miranda RL, Jia C, Delahanty J, Batra K, Keyes LR, Libster A, Wichmann R, Pereira TD, Benna MK, Tye KM. Social isolation recruits amygdala-cortical circuitry to escalate alcohol drinking. Res Sq 2024:rs.3.rs-4033115. [PMID: 38562728 PMCID: PMC10984017 DOI: 10.21203/rs.3.rs-4033115/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
How do social factors impact the brain and contribute to increased alcohol drinking? We found that social rank predicts alcohol drinking, where subordinates drink more than dominants. Furthermore, social isolation escalates alcohol drinking, particularly impacting subordinates who display a greater increase in alcohol drinking compared to dominants. Using cellular resolution calcium imaging, we show that the basolateral amygdala-medial prefrontal cortex (BLA-mPFC) circuit predicts alcohol drinking in a rank-dependent manner, unlike non-specific BLA activity. The BLA-mPFC circuit becomes hyperexcitable during social isolation, detecting social isolation states. Mimicking the observed increases in BLA-mPFC activity using optogenetics was sufficient to increase alcohol drinking, suggesting the BLA-mPFC circuit may be a neural substrate for the negative impact of social isolation. To test the hypothesis that the BLA-mPFC circuit conveys a signal induced by social isolation to motivate alcohol consumption, we first determined if this circuit detects social information. Leveraging optogenetics in combination with calcium imaging and computer vision pose tracking, we found that BLA-mPFC circuitry governs social behavior and neural representation of social contact. We further show that BLA-mPFC stimulation mimics social isolation-induced mPFC encoding of sucrose and alcohol, and inhibition of the BLA-mPFC circuit decreases alcohol drinking following social isolation. Collectively, these data suggest the amygdala-cortical circuit mirrors a neural encoding state similar to social isolation and underlies social isolation-associated alcohol drinking.
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Affiliation(s)
- Reesha R. Patel
- Salk Institute for Biological Studies, La Jolla, CA, USA
- Center for Psychiatric Neuroscience, Northwestern University, Chicago, IL, USA
| | | | - Kelly Kim
- Salk Institute for Biological Studies, La Jolla, CA, USA
- Howard Hughes at Salk Institute, La Jolla, CA, USA
| | | | - Felix H. Taschbach
- Salk Institute for Biological Studies, La Jolla, CA, USA
- University of California San Diego, La Jolla, CA, USA
| | - Hao Li
- Salk Institute for Biological Studies, La Jolla, CA, USA
- Center for Psychiatric Neuroscience, Northwestern University, Chicago, IL, USA
| | - Christopher R. Lee
- Salk Institute for Biological Studies, La Jolla, CA, USA
- University of California San Diego, La Jolla, CA, USA
| | - Aniek van Hoek
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Rogelio Castro
- Salk Institute for Biological Studies, La Jolla, CA, USA
- University of California San Diego, La Jolla, CA, USA
| | | | - Raymundo L. Miranda
- Salk Institute for Biological Studies, La Jolla, CA, USA
- University of California San Diego, La Jolla, CA, USA
| | - Caroline Jia
- Salk Institute for Biological Studies, La Jolla, CA, USA
- University of California San Diego, La Jolla, CA, USA
| | | | - Kanha Batra
- Salk Institute for Biological Studies, La Jolla, CA, USA
- University of California San Diego, La Jolla, CA, USA
| | - Laurel R. Keyes
- Salk Institute for Biological Studies, La Jolla, CA, USA
- Howard Hughes at Salk Institute, La Jolla, CA, USA
| | - Avraham Libster
- Salk Institute for Biological Studies, La Jolla, CA, USA
- University of California San Diego, La Jolla, CA, USA
| | - Romy Wichmann
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | | | - Kay M. Tye
- Salk Institute for Biological Studies, La Jolla, CA, USA
- University of California San Diego, La Jolla, CA, USA
- Howard Hughes at Salk Institute, La Jolla, CA, USA
- Howard Hughes Investigator and Wylie Vale Professor at Salk Institute, La Jolla, CA, USA
- Kavli Institute for the Brain and Mind, La Jolla, CA, USA
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2
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Kimchi EY, Burgos-Robles A, Matthews GA, Chakoma T, Patarino M, Weddington JC, Siciliano C, Yang W, Foutch S, Simons R, Fong MF, Jing M, Li Y, Polley DB, Tye KM. Reward contingency gates selective cholinergic suppression of amygdala neurons. eLife 2024; 12:RP89093. [PMID: 38376907 PMCID: PMC10942609 DOI: 10.7554/elife.89093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024] Open
Abstract
Basal forebrain cholinergic neurons modulate how organisms process and respond to environmental stimuli through impacts on arousal, attention, and memory. It is unknown, however, whether basal forebrain cholinergic neurons are directly involved in conditioned behavior, independent of secondary roles in the processing of external stimuli. Using fluorescent imaging, we found that cholinergic neurons are active during behavioral responding for a reward - even prior to reward delivery and in the absence of discrete stimuli. Photostimulation of basal forebrain cholinergic neurons, or their terminals in the basolateral amygdala (BLA), selectively promoted conditioned responding (licking), but not unconditioned behavior nor innate motor outputs. In vivo electrophysiological recordings during cholinergic photostimulation revealed reward-contingency-dependent suppression of BLA neural activity, but not prefrontal cortex. Finally, ex vivo experiments demonstrated that photostimulation of cholinergic terminals suppressed BLA projection neuron activity via monosynaptic muscarinic receptor signaling, while also facilitating firing in BLA GABAergic interneurons. Taken together, we show that the neural and behavioral effects of basal forebrain cholinergic activation are modulated by reward contingency in a target-specific manner.
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Affiliation(s)
- Eyal Y Kimchi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Neurology, Northwestern UniversityChicagoUnited States
| | - Anthony Burgos-Robles
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- The Department of Neuroscience, Developmental, and Regenerative Biology, Neuroscience Institute & Brain Health Consortium, University of Texas at San AntonioSan AntonioUnited States
| | - Gillian A Matthews
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Tatenda Chakoma
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Makenzie Patarino
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Javier C Weddington
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Cody Siciliano
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- Vanderbilt Center for Addiction Research, Department of Pharmacology, Vanderbilt UniversityNashvilleUnited States
| | - Wannan Yang
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Shaun Foutch
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Renee Simons
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Ming-fai Fong
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- Coulter Department of Biomedical Engineering, Georgia Tech & Emory UniversityAtlantaUnited States
| | - Miao Jing
- Chinese Institute for Brain ResearchBeijingChina
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences; PKUIDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life SciencesBeijingChina
| | - Daniel B Polley
- Eaton-Peabody Laboratories, Massachusetts Eye and EarBostonUnited States
- Department of Otolaryngology – Head and Neck Surgery, Harvard Medical SchoolBostonUnited States
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- HHMI Investigator, Member of the Kavli Institute for Brain and Mind, and Wylie Vale Professor at the Salk Institute for Biological StudiesLa JollaUnited States
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3
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LeDuke DO, Borio M, Miranda R, Tye KM. Anxiety and depression: A top-down, bottom-up model of circuit function. Ann N Y Acad Sci 2023; 1525:70-87. [PMID: 37129246 PMCID: PMC10695657 DOI: 10.1111/nyas.14997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
A functional interplay of bottom-up and top-down processing allows an individual to appropriately respond to the dynamic environment around them. These processing modalities can be represented as attractor states using a dynamical systems model of the brain. The transition probability to move from one attractor state to another is dependent on the stability, depth, neuromodulatory tone, and tonic changes in plasticity. However, how does the relationship between these states change in disease states, such as anxiety or depression? We describe bottom-up and top-down processing from Marr's computational-algorithmic-implementation perspective to understand depressive and anxious disease states. We illustrate examples of bottom-up processing as basolateral amygdala signaling and projections and top-down processing as medial prefrontal cortex internal signaling and projections. Understanding these internal processing dynamics can help us better model the multifaceted elements of anxiety and depression.
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Affiliation(s)
- Deryn O. LeDuke
- Salk Institute for Biological Studies, La Jolla, California, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, California, USA
| | - Matilde Borio
- Salk Institute for Biological Studies, La Jolla, California, USA
| | - Raymundo Miranda
- Salk Institute for Biological Studies, La Jolla, California, USA
- Neurosciences Graduate Program, University of California San Diego, La Jolla, California, USA
| | - Kay M. Tye
- Salk Institute for Biological Studies, La Jolla, California, USA
- Howard Hughes Medical Institute, La Jolla, California, USA
- Kavli Institute for the Brain and Mind, La Jolla, California, USA
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4
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Chen Z, Zhang R, Fang HS, Zhang YE, Bal A, Zhou H, Rock RR, Padilla-Coreano N, Keyes LR, Zhu H, Li YL, Komiyama T, Tye KM, Lu C. AlphaTracker: a multi-animal tracking and behavioral analysis tool. Front Behav Neurosci 2023; 17:1111908. [PMID: 37324523 PMCID: PMC10266280 DOI: 10.3389/fnbeh.2023.1111908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 02/21/2023] [Indexed: 06/17/2023] Open
Abstract
Computer vision has emerged as a powerful tool to elevate behavioral research. This protocol describes a computer vision machine learning pipeline called AlphaTracker, which has minimal hardware requirements and produces reliable tracking of multiple unmarked animals, as well as behavioral clustering. AlphaTracker pairs a top-down pose-estimation software combined with unsupervised clustering to facilitate behavioral motif discovery that will accelerate behavioral research. All steps of the protocol are provided as open-source software with graphic user interfaces or implementable with command-line prompts. Users with a graphical processing unit (GPU) can model and analyze animal behaviors of interest in less than a day. AlphaTracker greatly facilitates the analysis of the mechanism of individual/social behavior and group dynamics.
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Affiliation(s)
- Zexin Chen
- Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China
| | - Ruihan Zhang
- Zhiyuan College, Shanghai Jiao Tong University, Shanghai, China
- Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Hao-Shu Fang
- Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China
| | - Yu E. Zhang
- Department of Neurobiology, Center for Neural Circuits and Behavior, University of California, San Diego, La Jolla, CA, United States
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Aneesh Bal
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
- Salk Institute for Biological Studies, La Jolla, CA, United States
| | - Haowen Zhou
- Zhiyuan College, Shanghai Jiao Tong University, Shanghai, China
| | - Rachel R. Rock
- Salk Institute for Biological Studies, La Jolla, CA, United States
| | - Nancy Padilla-Coreano
- Salk Institute for Biological Studies, La Jolla, CA, United States
- Department of Neuroscience, University of Florida, Gainesville, FL, United States
| | - Laurel R. Keyes
- Salk Institute for Biological Studies, La Jolla, CA, United States
- Howard Hughes Medical Institute, The Salk Institute, La Jolla, CA, United States
| | - Haoyi Zhu
- Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China
| | - Yong-Lu Li
- Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China
| | - Takaki Komiyama
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Kay M. Tye
- Salk Institute for Biological Studies, La Jolla, CA, United States
- Howard Hughes Medical Institute, The Salk Institute, La Jolla, CA, United States
| | - Cewu Lu
- Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China
- Shanghai Artificial Intelligence Laboratory, Shanghai, China
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5
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Leppla CA, Keyes LR, Glober G, Matthews GA, Batra K, Jay M, Feng Y, Chen HS, Mills F, Delahanty J, Olson JM, Nieh EH, Namburi P, Wildes C, Wichmann R, Beyeler A, Kimchi EY, Tye KM. Thalamus sends information about arousal but not valence to the amygdala. Psychopharmacology (Berl) 2023; 240:477-499. [PMID: 36522481 PMCID: PMC9928937 DOI: 10.1007/s00213-022-06284-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 11/23/2022] [Indexed: 12/23/2022]
Abstract
RATIONALE The basolateral amygdala (BLA) and medial geniculate nucleus of the thalamus (MGN) have both been shown to be necessary for the formation of associative learning. While the role that the BLA plays in this process has long been emphasized, the MGN has been less well-studied and surrounded by debate regarding whether the relay of sensory information is active or passive. OBJECTIVES We seek to understand the role the MGN has within the thalamoamgydala circuit in the formation of associative learning. METHODS Here, we use optogenetics and in vivo electrophysiological recordings to dissect the MGN-BLA circuit and explore the specific subpopulations for evidence of learning and synthesis of information that could impact downstream BLA encoding. We employ various machine learning techniques to investigate function within neural subpopulations. We introduce a novel method to investigate tonic changes across trial-by-trial structure, which offers an alternative approach to traditional trial-averaging techniques. RESULTS We find that the MGN appears to encode arousal but not valence, unlike the BLA which encodes for both. We find that the MGN and the BLA appear to react differently to expected and unexpected outcomes; the BLA biased responses toward reward prediction error and the MGN focused on anticipated punishment. We uncover evidence of tonic changes by visualizing changes across trials during inter-trial intervals (baseline epochs) for a subset of cells. CONCLUSION We conclude that the MGN-BLA projector population acts as both filter and transferer of information by relaying information about the salience of cues to the amygdala, but these signals are not valence-specified.
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Affiliation(s)
- Chris A Leppla
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Laurel R Keyes
- Howard Hughes Medical Institute, The Salk Institute, La Jolla, CA, 92037, USA
- SNL-KT, Salk Institute for Biological Studies, 10010 N Torrey Pines Rd, La Jolla, CA, 92037, USA
| | - Gordon Glober
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Gillian A Matthews
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- SNL-KT, Salk Institute for Biological Studies, 10010 N Torrey Pines Rd, La Jolla, CA, 92037, USA
| | - Kanha Batra
- SNL-KT, Salk Institute for Biological Studies, 10010 N Torrey Pines Rd, La Jolla, CA, 92037, USA
| | - Maya Jay
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Yu Feng
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Hannah S Chen
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Fergil Mills
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- SNL-KT, Salk Institute for Biological Studies, 10010 N Torrey Pines Rd, La Jolla, CA, 92037, USA
| | - Jeremy Delahanty
- Howard Hughes Medical Institute, The Salk Institute, La Jolla, CA, 92037, USA
- SNL-KT, Salk Institute for Biological Studies, 10010 N Torrey Pines Rd, La Jolla, CA, 92037, USA
| | - Jacob M Olson
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Edward H Nieh
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Praneeth Namburi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Craig Wildes
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Romy Wichmann
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
- SNL-KT, Salk Institute for Biological Studies, 10010 N Torrey Pines Rd, La Jolla, CA, 92037, USA
| | - Anna Beyeler
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Eyal Y Kimchi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA, 02139, USA.
- Howard Hughes Medical Institute, The Salk Institute, La Jolla, CA, 92037, USA.
- SNL-KT, Salk Institute for Biological Studies, 10010 N Torrey Pines Rd, La Jolla, CA, 92037, USA.
- Kavli Institute for Brain and Mind, 10010 North Torrey Pines Road, La Jolla, CA, 92037, USA.
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6
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Abstract
Social signals can serve as potent emotional triggers with powerful impacts on processes from cognition to valence processing. How are social signals dynamically and flexibly associated with positive or negative valence? How do our past social experiences and present social standing shape our motivation to seek or avoid social contact? We discuss a model in which social attributes, social history, social memory, social rank and social isolation can flexibly influence valence assignment to social stimuli, termed here as 'social valence'. We emphasize how the brain encodes each of these four factors and highlight the neural circuits and mechanisms that play a part in the perception of social attributes, social memory and social rank, as well as how these factors affect valence systems associated with social stimuli. We highlight the impact of social isolation, dissecting the neural and behavioural mechanisms that mediate the effects of acute versus prolonged periods of social isolation. Importantly, we discuss conceptual models that may account for the potential shift in valence of social stimuli from positive to negative as the period of isolation extends in time. Collectively, this Review identifies factors that control the formation and attribution of social valence - integrating diverse areas of research and emphasizing their unique contributions to the categorization of social stimuli as positive or negative.
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Affiliation(s)
- Nancy Padilla-Coreano
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Kay M Tye
- HHMI-Salk Institute for Biological Studies, La Jolla, CA, USA.
| | - Moriel Zelikowsky
- Department of Neurobiology, School of Medicine, University of Utah, Salt Lake City, UT, USA
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7
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Li H, Namburi P, Olson JM, Borio M, Lemieux ME, Beyeler A, Calhoon GG, Hitora-Imamura N, Coley AA, Libster A, Bal A, Jin X, Wang H, Jia C, Choudhury SR, Shi X, Felix-Ortiz AC, de la Fuente V, Barth VP, King HO, Izadmehr EM, Revanna JS, Batra K, Fischer KB, Keyes LR, Padilla-Coreano N, Siciliano CA, McCullough KM, Wichmann R, Ressler KJ, Fiete IR, Zhang F, Li Y, Tye KM. Neurotensin orchestrates valence assignment in the amygdala. Nature 2022; 608:586-592. [PMID: 35859170 PMCID: PMC9583860 DOI: 10.1038/s41586-022-04964-y] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Accepted: 06/10/2022] [Indexed: 02/03/2023]
Abstract
The ability to associate temporally segregated information and assign positive or negative valence to environmental cues is paramount for survival. Studies have shown that different projections from the basolateral amygdala (BLA) are potentiated following reward or punishment learning1-7. However, we do not yet understand how valence-specific information is routed to the BLA neurons with the appropriate downstream projections, nor do we understand how to reconcile the sub-second timescales of synaptic plasticity8-11 with the longer timescales separating the predictive cues from their outcomes. Here we demonstrate that neurotensin (NT)-expressing neurons in the paraventricular nucleus of the thalamus (PVT) projecting to the BLA (PVT-BLA:NT) mediate valence assignment by exerting NT concentration-dependent modulation in BLA during associative learning. We found that optogenetic activation of the PVT-BLA:NT projection promotes reward learning, whereas PVT-BLA projection-specific knockout of the NT gene (Nts) augments punishment learning. Using genetically encoded calcium and NT sensors, we further revealed that both calcium dynamics within the PVT-BLA:NT projection and NT concentrations in the BLA are enhanced after reward learning and reduced after punishment learning. Finally, we showed that CRISPR-mediated knockout of the Nts gene in the PVT-BLA pathway blunts BLA neural dynamics and attenuates the preference for active behavioural strategies to reward and punishment predictive cues. In sum, we have identified NT as a neuropeptide that signals valence in the BLA, and showed that NT is a critical neuromodulator that orchestrates positive and negative valence assignment in amygdala neurons by extending valence-specific plasticity to behaviourally relevant timescales.
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Affiliation(s)
- Hao Li
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Praneeth Namburi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jacob M Olson
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Neuroscience Program, Department of Psychology, Volen National Center for Complex Systems, Brandeis University, Waltham, MA, USA
| | - Matilde Borio
- Salk Institute for Biological Studies, La Jolla, CA, USA
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Mackenzie E Lemieux
- Salk Institute for Biological Studies, La Jolla, CA, USA
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Anna Beyeler
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- University of Bordeaux, Neurocentre Magendie, INSERM 1215, Bordeaux, France
| | - Gwendolyn G Calhoon
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Neuroscience Program, Bates College, Lewiston, ME, USA
| | - Natsuko Hitora-Imamura
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Pharmacology, Graduate School of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan
- Graduate School of Pharmaceutical Sciences, Kumamoto University, Kumamoto, Japan
| | - Austin A Coley
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Avraham Libster
- Salk Institute for Biological Studies, La Jolla, CA, USA
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Aneesh Bal
- Salk Institute for Biological Studies, La Jolla, CA, USA
- Behavioral Neuroscience, Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Xin Jin
- Society of Fellows, Harvard University, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Huan Wang
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Peking-Tsinghua Center for Life Science, IDG/McGovern Institute for Brain Research at PKU, Beijing, China
| | - Caroline Jia
- Salk Institute for Biological Studies, La Jolla, CA, USA
- Neuroscience Graduate Program, University of California San Diego, La Jolla, CA, USA
| | | | - Xi Shi
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ada C Felix-Ortiz
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Verónica de la Fuente
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Instituto de Fisiología, Biología Molecular y Neurociencias (IFIBYNE-UBA-CONICET), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
- Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Vanessa P Barth
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Electrical and Computer Engineering, Technical University of Munich, Munich, Germany
| | - Hunter O King
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Whitehead Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ehsan M Izadmehr
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jasmin S Revanna
- Salk Institute for Biological Studies, La Jolla, CA, USA
- Biological Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Kanha Batra
- Salk Institute for Biological Studies, La Jolla, CA, USA
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
| | - Kyle B Fischer
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Laurel R Keyes
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Cody A Siciliano
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Vanderbilt Center for Addiction Research, Department of Pharmacology, Vanderbilt University, Nashville, TN, USA
| | - Kenneth M McCullough
- Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Romy Wichmann
- Salk Institute for Biological Studies, La Jolla, CA, USA
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kerry J Ressler
- Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Ila R Fiete
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Feng Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Cambridge, MA, USA
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Peking-Tsinghua Center for Life Science, IDG/McGovern Institute for Brain Research at PKU, Beijing, China
| | - Kay M Tye
- Salk Institute for Biological Studies, La Jolla, CA, USA.
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Systems Neuroscience Laboratory and Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, CA, USA.
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8
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Dwortz MF, Curley JP, Tye KM, Padilla-Coreano N. Neural systems that facilitate the representation of social rank. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200444. [PMID: 35000438 PMCID: PMC8743891 DOI: 10.1098/rstb.2020.0444] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Accepted: 11/10/2021] [Indexed: 12/15/2022] Open
Abstract
Across species, animals organize into social dominance hierarchies that serve to decrease aggression and facilitate survival of the group. Neuroscientists have adopted several model organisms to study dominance hierarchies in the laboratory setting, including fish, reptiles, rodents and primates. We review recent literature across species that sheds light onto how the brain represents social rank to guide socially appropriate behaviour within a dominance hierarchy. First, we discuss how the brain responds to social status signals. Then, we discuss social approach and avoidance learning mechanisms that we propose could drive rank-appropriate behaviour. Lastly, we discuss how the brain represents memories of individuals (social memory) and how this may support the maintenance of unique individual relationships within a social group. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.
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Affiliation(s)
- Madeleine F. Dwortz
- Department of Psychology, University of Texas at Austin, Austin, TX 78712, USA
- Institute for Neuroscience, University of Texas at Austin, Austin, TX 78712, USA
| | - James P. Curley
- Department of Psychology, University of Texas at Austin, Austin, TX 78712, USA
| | - Kay M. Tye
- Systems Neuroscience Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nancy Padilla-Coreano
- Systems Neuroscience Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Department of Neuroscience, University of Florida, Gainesville, FN 32611, USA
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9
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Lee CR, Chen A, Tye KM. The neural circuitry of social homeostasis: Consequences of acute versus chronic social isolation. Cell 2021; 184:2794-2795. [PMID: 33989550 DOI: 10.1016/j.cell.2021.04.044] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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10
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Lee CR, Chen A, Tye KM. The neural circuitry of social homeostasis: Consequences of acute versus chronic social isolation. Cell 2021; 184:1500-1516. [PMID: 33691140 PMCID: PMC8580010 DOI: 10.1016/j.cell.2021.02.028] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 01/29/2021] [Accepted: 02/09/2021] [Indexed: 11/22/2022]
Abstract
Social homeostasis is the ability of individuals to detect the quantity and quality of social contact, compare it to an established set-point in a command center, and adjust the effort expended to seek the optimal social contact expressed via an effector system. Social contact becomes a positive or negative valence stimulus when it is deficient or in excess, respectively. Chronic deficits lead to set-point adaptations such that reintroduction to the previous optimum is experienced as a surplus. Here, we build upon previous models for social homeostasis to include adaptations to lasting changes in environmental conditions, such as with chronic isolation.
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Affiliation(s)
- Christopher R Lee
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA
| | - Alon Chen
- Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Kay M Tye
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA.
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11
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Coley AA, Padilla-Coreano N, Patel R, Tye KM. Valence processing in the PFC: Reconciling circuit-level and systems-level views. Int Rev Neurobiol 2021; 158:171-212. [PMID: 33785145 DOI: 10.1016/bs.irn.2020.12.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
An essential component in animal behavior is the ability to process emotion and dissociate among positive and negative valence in response to a rewarding or aversive stimulus. The medial prefrontal cortex (mPFC)-responsible for higher order executive functions that include cognition, learning, and working memory; and is also involved in sociability-plays a major role in emotional processing and control. Although the amygdala is widely regarded as the "emotional hub," the mPFC encodes for context-specific salience and elicits top-down control over limbic circuitry. The mPFC can then conduct behavioral responses, via cortico-striatal and cortico-brainstem pathways, that correspond to emotional stimuli. Evidence shows that abnormalities within the mPFC lead to sociability deficits, working memory impairments, and drug-seeking behavior that include addiction and compulsive disorders; as well as conditions such as anhedonia. Recent studies investigate the effects of aberrant salience processing on cortical circuitry and neuronal populations associated with these behaviors. In this chapter, we discuss mPFC valence processing, neuroanatomical connections, and physiological substrates involved in mPFC-associated behavior. We review neurocomputational and theoretical models such as "mixed selectivity," that describe cognitive control, attentiveness, and motivational drives. Using this knowledge, we describe the effects of valence imbalances and its influence on mPFC neural pathways that contribute to deficits in social cognition, while understanding the effects in addiction/compulsive behaviors and anhedonia.
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Affiliation(s)
- Austin A Coley
- Salk Institute for Biological Studies, La Jolla, CA, United States
| | | | - Reesha Patel
- Salk Institute for Biological Studies, La Jolla, CA, United States
| | - Kay M Tye
- Salk Institute for Biological Studies, La Jolla, CA, United States.
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12
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Tsuda B, Tye KM, Siegelmann HT, Sejnowski TJ. A modeling framework for adaptive lifelong learning with transfer and savings through gating in the prefrontal cortex. Proc Natl Acad Sci U S A 2020; 117:29872-29882. [PMID: 33154155 PMCID: PMC7703668 DOI: 10.1073/pnas.2009591117] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
The prefrontal cortex encodes and stores numerous, often disparate, schemas and flexibly switches between them. Recent research on artificial neural networks trained by reinforcement learning has made it possible to model fundamental processes underlying schema encoding and storage. Yet how the brain is able to create new schemas while preserving and utilizing old schemas remains unclear. Here we propose a simple neural network framework that incorporates hierarchical gating to model the prefrontal cortex's ability to flexibly encode and use multiple disparate schemas. We show how gating naturally leads to transfer learning and robust memory savings. We then show how neuropsychological impairments observed in patients with prefrontal damage are mimicked by lesions of our network. Our architecture, which we call DynaMoE, provides a fundamental framework for how the prefrontal cortex may handle the abundance of schemas necessary to navigate the real world.
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Affiliation(s)
- Ben Tsuda
- Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037;
- Neurosciences Graduate Program, University of California San Diego, La Jolla, CA 92093
- Medical Scientist Training Program, University of California San Diego, La Jolla, CA 92093
| | - Kay M Tye
- Systems Neuroscience Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037
| | - Hava T Siegelmann
- Biologically Inspired Neural & Dynamical Systems Laboratory, School of Computer Science, University of Massachusetts Amherst, Amherst, MA, 01003
| | - Terrence J Sejnowski
- Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037;
- Institute for Neural Computation, University of California San Diego, La Jolla, CA 92093
- Division of Biological Sciences, University of California San Diego, La Jolla, CA 92093
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13
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Tomova L, Wang KL, Thompson T, Matthews GA, Takahashi A, Tye KM, Saxe R. Acute social isolation evokes midbrain craving responses similar to hunger. Nat Neurosci 2020; 23:1597-1605. [DOI: 10.1038/s41593-020-00742-z] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 10/15/2020] [Indexed: 12/12/2022]
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14
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Wu A, Yu B, Chen Q, Matthews GA, Lu C, Campbell E, Tye KM, Komiyama T. Context-dependent plasticity of adult-born neurons regulated by cortical feedback. Sci Adv 2020; 6:6/42/eabc8319. [PMID: 33067236 PMCID: PMC7567600 DOI: 10.1126/sciadv.abc8319] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Accepted: 09/02/2020] [Indexed: 05/26/2023]
Abstract
In a complex and dynamic environment, the brain flexibly adjusts its circuits to preferentially process behaviorally relevant information. Here, we investigated how the olfactory bulb copes with this demand by examining the plasticity of adult-born granule cells (abGCs). We found that learning of olfactory discrimination elevates odor responses of young abGCs and increases their apical dendritic spines. This plasticity did not occur in abGCs during passive odor experience nor in resident granule cells (rGCs) during learning. Furthermore, we found that feedback projections from the piriform cortex show elevated activity during learning, and activating piriform feedback elicited stronger excitatory postsynaptic currents in abGCs than rGCs. Inactivation of piriform feedback blocked abGC plasticity during learning, and activation of piriform feedback during passive experience induced learning-like plasticity of abGCs. Our work describes a neural circuit mechanism that uses adult neurogenesis to update a sensory circuit to flexibly adapt to new behavioral demands.
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Affiliation(s)
- An Wu
- Neurobiology Section, and Center for Neural Circuits and Behavior, University of California San Diego, La Jolla, CA 92093, USA.
- Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 92093, USA
| | - Bin Yu
- Neurobiology Section, and Center for Neural Circuits and Behavior, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 92093, USA
- Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Qiyu Chen
- Neurobiology Section, and Center for Neural Circuits and Behavior, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 92093, USA
| | | | - Chen Lu
- Neurobiology Section, and Center for Neural Circuits and Behavior, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 92093, USA
| | - Evan Campbell
- Neurobiology Section, and Center for Neural Circuits and Behavior, University of California San Diego, La Jolla, CA 92093, USA
| | - Kay M Tye
- Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Takaki Komiyama
- Neurobiology Section, and Center for Neural Circuits and Behavior, University of California San Diego, La Jolla, CA 92093, USA.
- Department of Neurosciences, and Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA 92093, USA
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15
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Shemesh OA, Linghu C, Piatkevich KD, Goodwin D, Celiker OT, Gritton HJ, Romano MF, Gao R, Yu CCJ, Tseng HA, Bensussen S, Narayan S, Yang CT, Freifeld L, Siciliano CA, Gupta I, Wang J, Pak N, Yoon YG, Ullmann JFP, Guner-Ataman B, Noamany H, Sheinkopf ZR, Park WM, Asano S, Keating AE, Trimmer JS, Reimer J, Tolias AS, Bear MF, Tye KM, Han X, Ahrens MB, Boyden ES. Precision Calcium Imaging of Dense Neural Populations via a Cell-Body-Targeted Calcium Indicator. Neuron 2020; 107:470-486.e11. [PMID: 32592656 DOI: 10.1016/j.neuron.2020.05.029] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 05/09/2019] [Accepted: 05/20/2020] [Indexed: 01/11/2023]
Abstract
Methods for one-photon fluorescent imaging of calcium dynamics can capture the activity of hundreds of neurons across large fields of view at a low equipment complexity and cost. In contrast to two-photon methods, however, one-photon methods suffer from higher levels of crosstalk from neuropil, resulting in a decreased signal-to-noise ratio and artifactual correlations of neural activity. We address this problem by engineering cell-body-targeted variants of the fluorescent calcium indicators GCaMP6f and GCaMP7f. We screened fusions of GCaMP to natural, as well as artificial, peptides and identified fusions that localized GCaMP to within 50 μm of the cell body of neurons in mice and larval zebrafish. One-photon imaging of soma-targeted GCaMP in dense neural circuits reported fewer artifactual spikes from neuropil, an increased signal-to-noise ratio, and decreased artifactual correlation across neurons. Thus, soma-targeting of fluorescent calcium indicators facilitates usage of simple, powerful, one-photon methods for imaging neural calcium dynamics.
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Affiliation(s)
- Or A Shemesh
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; Department of Biological Engineering, MIT, Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; Department of Neurobiology and Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Changyang Linghu
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
| | - Kiryl D Piatkevich
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; Department of Biological Engineering, MIT, Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China
| | - Daniel Goodwin
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Orhan Tunc Celiker
- MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
| | - Howard J Gritton
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
| | - Michael F Romano
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
| | - Ruixuan Gao
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Chih-Chieh Jay Yu
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; Department of Biological Engineering, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Hua-An Tseng
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
| | - Seth Bensussen
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
| | - Sujatha Narayan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Chao-Tsung Yang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Limor Freifeld
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; Faculty of Biomedical Engineering, Technion, Haifa, Israel
| | - Cody A Siciliano
- Vanderbilt Center for Addiction Research, Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
| | - Ishan Gupta
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; Department of Biological Engineering, MIT, Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Joyce Wang
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Nikita Pak
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; Department of Mechanical Engineering, MIT, Cambridge, MA, USA
| | - Young-Gyu Yoon
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA; School of Electrical Engineering, KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea
| | - Jeremy F P Ullmann
- Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital & Harvard Medical School, Boston, MA, USA
| | - Burcu Guner-Ataman
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | - Habiba Noamany
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Zoe R Sheinkopf
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Shoh Asano
- Internal Medicine Research Unit, Pfizer, Cambridge, MA, USA
| | - Amy E Keating
- Department of Biological Engineering, MIT, Cambridge, MA, USA; Department of Biology, MIT, Cambridge, MA, USA; Koch Institute, MIT, Cambridge, MA 02139, USA
| | - James S Trimmer
- Department of Physiology and Membrane Biology, University of California, Davis School of Medicine, Davis, CA, USA
| | - Jacob Reimer
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA; Center for Neuroscience and AI, Baylor College of Medicine, Houston, TX, USA
| | - Andreas S Tolias
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, USA; Center for Neuroscience and AI, Baylor College of Medicine, Houston, TX, USA; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Mark F Bear
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Xue Han
- Boston University, Department of Biomedical Engineering, Boston, MA 02215, USA
| | - Misha B Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Edward S Boyden
- The MIT Media Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA; Department of Biological Engineering, MIT, Cambridge, MA, USA; MIT Center for Neurobiological Engineering, MIT, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA; MIT McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; Koch Institute, MIT, Cambridge, MA 02139, USA.
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16
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Siciliano CA, Noamany H, Chang CJ, Brown AR, Chen X, Leible D, Lee JJ, Wang J, Vernon AN, Vander Weele CM, Kimchi EY, Heiman M, Tye KM. A cortical-brainstem circuit predicts and governs compulsive alcohol drinking. Science 2020; 366:1008-1012. [PMID: 31754002 DOI: 10.1126/science.aay1186] [Citation(s) in RCA: 113] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 10/04/2019] [Indexed: 12/31/2022]
Abstract
What individual differences in neural activity predict the future escalation of alcohol drinking from casual to compulsive? The neurobiological mechanisms that gate the transition from moderate to compulsive drinking remain poorly understood. We longitudinally tracked the development of compulsive drinking across a binge-drinking experience in male mice. Binge drinking unmasked individual differences, revealing latent traits in alcohol consumption and compulsive drinking despite equal prior exposure to alcohol. Distinct neural activity signatures of cortical neurons projecting to the brainstem before binge drinking predicted the ultimate emergence of compulsivity. Mimicry of activity patterns that predicted drinking phenotypes was sufficient to bidirectionally modulate drinking. Our results provide a mechanistic explanation for individual variance in vulnerability to compulsive alcohol drinking.
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Affiliation(s)
- Cody A Siciliano
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. .,Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.,Vanderbilt Center for Addiction Research, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Habiba Noamany
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Chia-Jung Chang
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alex R Brown
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.,Vanderbilt Center for Addiction Research, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Xinhong Chen
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Daniel Leible
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jennifer J Lee
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Joyce Wang
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Amanda N Vernon
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Caitlin M Vander Weele
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Eyal Y Kimchi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Myriam Heiman
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. .,The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
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17
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Padilla-Coreano N, Canetta S, Mikofsky RM, Alway E, Passecker J, Myroshnychenko MV, Garcia-Garcia AL, Warren R, Teboul E, Blackman DR, Morton MP, Hupalo S, Tye KM, Kellendonk C, Kupferschmidt DA, Gordon JA. Hippocampal-Prefrontal Theta Transmission Regulates Avoidance Behavior. Neuron 2019; 104:601-610.e4. [PMID: 31521441 DOI: 10.1016/j.neuron.2019.08.006] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 06/08/2019] [Accepted: 08/03/2019] [Indexed: 12/23/2022]
Abstract
Long-range synchronization of neural oscillations correlates with distinct behaviors, yet its causal role remains unproven. In mice, tests of avoidance behavior evoke increases in theta-frequency (∼8 Hz) oscillatory synchrony between the ventral hippocampus (vHPC) and medial prefrontal cortex (mPFC). To test the causal role of this synchrony, we dynamically modulated vHPC-mPFC terminal activity using optogenetic stimulation. Oscillatory stimulation at 8 Hz maximally increased avoidance behavior compared to 2, 4, and 20 Hz. Moreover, avoidance behavior was selectively increased when 8-Hz stimulation was delivered in an oscillatory, but not pulsatile, manner. Furthermore, 8-Hz oscillatory stimulation enhanced vHPC-mPFC neurotransmission and entrained neural activity in the vHPC-mPFC network, resulting in increased synchrony between vHPC theta activity and mPFC spiking. These data suggest a privileged role for vHPC-mPFC theta-frequency communication in generating avoidance behavior and provide direct evidence that synchronized oscillations play a role in facilitating neural transmission and behavior.
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Affiliation(s)
- Nancy Padilla-Coreano
- Systems Neuroscience Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Sarah Canetta
- Department of Psychiatry, Columbia University Medical Center, 1051 Riverside Drive, New York, NY 10032, USA; Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Rachel M Mikofsky
- Integrative Neuroscience Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA
| | - Emily Alway
- Integrative Neuroscience Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA
| | - Johannes Passecker
- Integrative Neuroscience Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA; Zuckerman Mind Brain Behavior Institute, New York, NY 10027, USA
| | - Maxym V Myroshnychenko
- Integrative Neuroscience Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA
| | - Alvaro L Garcia-Garcia
- Department of Psychiatry, Columbia University Medical Center, 1051 Riverside Drive, New York, NY 10032, USA
| | - Richard Warren
- Department of Psychiatry, Columbia University Medical Center, 1051 Riverside Drive, New York, NY 10032, USA
| | - Eric Teboul
- Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY 10032, USA
| | - Dakota R Blackman
- Department of Psychiatry, Columbia University Medical Center, 1051 Riverside Drive, New York, NY 10032, USA
| | - Mitchell P Morton
- Department of Psychiatry, Columbia University Medical Center, 1051 Riverside Drive, New York, NY 10032, USA
| | - Sofiya Hupalo
- Integrative Neuroscience Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA
| | - Kay M Tye
- Systems Neuroscience Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Christoph Kellendonk
- Department of Psychiatry, Columbia University Medical Center, 1051 Riverside Drive, New York, NY 10032, USA; Department of Pharmacology, Columbia University Medical Center, 1051 Riverside Drive, New York, NY 10032, USA; Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY 10032, USA
| | - David A Kupferschmidt
- Integrative Neuroscience Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA
| | - Joshua A Gordon
- Integrative Neuroscience Section, National Institute of Neurological Disorders and Stroke, NIH, Bethesda, MD 20892, USA; National Institute of Mental Health, NIH, Bethesda, MD 20892, USA.
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18
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Abstract
How do our brains determine whether something is good or bad? How is this computational goal implemented in biological systems? Given the critical importance of valence processing for survival, the brain has evolved multiple strategies to solve this problem at different levels. The psychological concept of "emotional valence" is now beginning to find grounding in neuroscience. This review aims to bridge the gap between psychology and neuroscience on the topic of emotional valence processing. Here, I highlight a subset of studies that exemplify circuit motifs that repeatedly appear as implementational systems in valence processing. The motifs I identify as being important in valence processing include (1) Labeled Lines, (2) Divergent Paths, (3) Opposing Components, and (4) Neuromodulatory Gain. Importantly, the functionality of neural substrates in valence processing is dynamic, context-dependent, and changing across short and long timescales due to synaptic plasticity, competing mechanisms, and homeostatic need.
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Affiliation(s)
- Kay M Tye
- Picower Institute for Learning and Memory, Dept of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Salk Institute for Biological Sciences, La Jolla, CA 92037, USA.
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19
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Abstract
There is disagreement on how best to define and investigate fear. Nature Neuroscience asked Dean Mobbs to lead experts from the fields of human and animal affective neuroscience to discuss their viewpoints on how to define fear and how to move forward with the study of fear.
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Affiliation(s)
- Dean Mobbs
- Department of Humanities and Social Sciences and Computation and Neural Systems Program, California Institute of Technology, Pasadena, California, USA.
| | - Ralph Adolphs
- Department of Humanities and Social Sciences and Computation and Neural Systems Program, California Institute of Technology, Pasadena, California, USA
| | - Michael S Fanselow
- Departments of Psychology and Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California, USA
| | - Lisa Feldman Barrett
- Department of Psychology, Northeastern University, Boston, Massachusetts, USA
- Martinos Center for Biomedical Imaging and Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Joseph E LeDoux
- Center for Neural Science, New York University, New York, New York, USA
- Nathan Kline Institute, New York State Office of Mental Health, New York, New York, USA
- Departments of Psychiatry and Child and Adolescent Psychiatry, NYU Langone Medical School, New York, New York, USA
| | - Kerry Ressler
- Division of Depression & Anxiety Disorders, McLean Hospital, Belmont, Massachusetts, USA
- Department of Psychiatry at Harvard Medical School, Boston, Massachusetts, USA
| | - Kay M Tye
- Salk Institute for Biological Studies, La Jolla, California, USA
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20
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Abstract
Social connections are vital to survival throughout the animal kingdom and are dynamic across the life span. There are debilitating consequences of social isolation and loneliness, and social support is increasingly a primary consideration in health care, disease prevention, and recovery. Considering social connection as an "innate need," it is hypothesized that evolutionarily conserved neural systems underlie the maintenance of social connections: alerting the individual to their absence and coordinating effector mechanisms to restore social contact. This is reminiscent of a homeostatic system designed to maintain social connection. Here, we explore the identity of neural systems regulating "social homeostasis." We review findings from rodent studies evaluating the rapid response to social deficit (in the form of acute social isolation) and propose that parallel, overlapping circuits are engaged to adapt to the vulnerabilities of isolation and restore social connection. By considering the neural systems regulating other homeostatic needs, such as energy and fluid balance, we discuss the potential attributes of social homeostatic circuitry. We reason that uncovering the identity of these circuits/mechanisms will facilitate our understanding of how loneliness perpetuates long-term disease states, which we speculate may result from sustained recruitment of social homeostatic circuits.
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Affiliation(s)
- Gillian A Matthews
- Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Kay M Tye
- Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts.,The Salk Institute for Biological Sciences, La Jolla, California
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21
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Abstract
Alcohol and drug use can dysregulate neural circuit function to produce a wide range of neuropsychiatric disorders, including addiction. To understand the neural circuit computations that mediate behavior, and how substances of abuse may transform them, we must first be able to observe the activity of circuits. While many techniques have been utilized to measure activity in specific brain regions, these regions are made up of heterogeneous sub-populations, and assessing activity from neuronal populations of interest has been an ongoing challenge. To fully understand how neural circuits mediate addiction-related behavior, we must be able to reveal the cellular granularity within brain regions and circuits by overlaying functional information with the genetic and anatomical identity of the cells involved. The development of genetically encoded calcium indicators, which can be targeted to populations of interest, allows for in vivo visualization of calcium dynamics, a proxy for neuronal activity, thus providing an avenue for real-time assessment of activity in genetically and anatomically defined populations during behavior. Here, we highlight recent advances in calcium imaging technology, compare the current technology with other state-of-the-art approaches for in vivo monitoring of neural activity, and discuss the strengths, limitations, and practical concerns for observing neural circuit activity in preclinical addiction models.
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Affiliation(s)
- Cody A Siciliano
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States; The Salk Institute for Biological Sciences, 10010 N Torrey Pines Road, La Jolla, CA 92037, United States.
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22
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Weele CMV, Siciliano CA, Tye KM. Dopamine tunes prefrontal outputs to orchestrate aversive processing. Brain Res 2018; 1713:16-31. [PMID: 30513287 DOI: 10.1016/j.brainres.2018.11.044] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 11/25/2018] [Accepted: 11/30/2018] [Indexed: 01/06/2023]
Abstract
Decades of research suggest that the mesocortical dopamine system exerts powerful control over mPFC physiology and function. Indeed, dopamine signaling in the medial prefrontal cortex (mPFC) is implicated in a vast array of processes, including working memory, stimulus discrimination, stress responses, and emotional and behavioral control. Consequently, even slight perturbations within this delicate system result in profound disruptions of mPFC-mediated processes. Many neuropsychiatric disorders are associated with dysregulation of mesocortical dopamine, including schizophrenia, depression, attention deficit hyperactivity disorder, post-traumatic stress disorder, among others. Here, we review the anatomy and functions of the mesocortical dopamine system. In contrast to the canonical role of striatal dopamine in reward-related functions, recent work has revealed that mesocortical dopamine fine-tunes distinct efferent projection populations in a manner that biases subsequent behavior towards responding to stimuli associated with potentially aversive outcomes. We propose a framework wherein dopamine can serve as a signal for switching mPFC states by orchestrating how information is routed to the rest of the brain.
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Affiliation(s)
- Caitlin M Vander Weele
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Cody A Siciliano
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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23
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Siciliano CA, Mills F, Tye KM. Double threat in striatal dopamine signaling. Nat Neurosci 2018; 21:1296-1297. [PMID: 30258236 DOI: 10.1038/s41593-018-0243-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Cody A Siciliano
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Fergil Mills
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.,The Salk Institute for Biological Sciences, La Jolla, CA, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA. .,The Salk Institute for Biological Sciences, La Jolla, CA, USA.
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24
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Allsop SA, Wichmann R, Mills F, Burgos-Robles A, Chang CJ, Felix-Ortiz AC, Vienne A, Beyeler A, Izadmehr EM, Glober G, Cum MI, Stergiadou J, Anandalingam KK, Farris K, Namburi P, Leppla CA, Weddington JC, Nieh EH, Smith AC, Ba D, Brown EN, Tye KM. Corticoamygdala Transfer of Socially Derived Information Gates Observational Learning. Cell 2018; 173:1329-1342.e18. [PMID: 29731170 DOI: 10.1016/j.cell.2018.04.004] [Citation(s) in RCA: 166] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Revised: 12/27/2017] [Accepted: 04/03/2018] [Indexed: 01/15/2023]
Abstract
Observational learning is a powerful survival tool allowing individuals to learn about threat-predictive stimuli without directly experiencing the pairing of the predictive cue and punishment. This ability has been linked to the anterior cingulate cortex (ACC) and the basolateral amygdala (BLA). To investigate how information is encoded and transmitted through this circuit, we performed electrophysiological recordings in mice observing a demonstrator mouse undergo associative fear conditioning and found that BLA-projecting ACC (ACC→BLA) neurons preferentially encode socially derived aversive cue information. Inhibition of ACC→BLA alters real-time amygdala representation of the aversive cue during observational conditioning. Selective inhibition of the ACC→BLA projection impaired acquisition, but not expression, of observational fear conditioning. We show that information derived from observation about the aversive value of the cue is transmitted from the ACC to the BLA and that this routing of information is critically instructive for observational fear conditioning. VIDEO ABSTRACT.
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Affiliation(s)
- Stephen A Allsop
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Romy Wichmann
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Fergil Mills
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Anthony Burgos-Robles
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Chia-Jung Chang
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ada C Felix-Ortiz
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alienor Vienne
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Anna Beyeler
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ehsan M Izadmehr
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gordon Glober
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Meghan I Cum
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Johanna Stergiadou
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kavitha K Anandalingam
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kathryn Farris
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Praneeth Namburi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Christopher A Leppla
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Javier C Weddington
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Edward H Nieh
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Anne C Smith
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ 85724, USA
| | - Demba Ba
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Emery N Brown
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA; The Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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25
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26
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Chatterjee S, Sullivan HA, MacLennan BJ, Xu R, Hou Y, Lavin TK, Lea NE, Michalski JE, Babcock KR, Dietrich S, Matthews GA, Beyeler A, Calhoon GG, Glober G, Whitesell JD, Yao S, Cetin A, Harris JA, Zeng H, Tye KM, Reid RC, Wickersham IR. Nontoxic, double-deletion-mutant rabies viral vectors for retrograde targeting of projection neurons. Nat Neurosci 2018; 21:638-646. [PMID: 29507411 PMCID: PMC6503322 DOI: 10.1038/s41593-018-0091-7] [Citation(s) in RCA: 108] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2017] [Accepted: 01/14/2018] [Indexed: 12/25/2022]
Abstract
Recombinant rabies viral vectors have proven useful for applications including retrograde targeting of projection neurons and monosynaptic tracing, but their cytotoxicity has limited their use to short-term experiments. Here we introduce a new class of double-deletion-mutant rabies viral vectors that left transduced cells alive and healthy indefinitely. Deletion of the viral polymerase gene abolished cytotoxicity and reduced transgene expression to trace levels but left vectors still able to retrogradely infect projection neurons and express recombinases, allowing downstream expression of other transgene products such as fluorophores and calcium indicators. The morphology of retrogradely targeted cells appeared unperturbed at 1 year postinjection. Whole-cell patch-clamp recordings showed no physiological abnormalities at 8 weeks. Longitudinal two-photon structural and functional imaging in vivo, tracking thousands of individual neurons for up to 4 months, showed that transduced neurons did not die but retained stable visual response properties even at the longest time points imaged.
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Affiliation(s)
| | - Heather A Sullivan
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Ran Xu
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - YuanYuan Hou
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Thomas K Lavin
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Nicholas E Lea
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jacob E Michalski
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kelsey R Babcock
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stephan Dietrich
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Gillian A Matthews
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Anna Beyeler
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Gwendolyn G Calhoon
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Gordon Glober
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Shenqin Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Ali Cetin
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Kay M Tye
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - R Clay Reid
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Ian R Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
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27
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Abstract
A fundamental problem in neuroscience is to characterize the dynamics of spiking from the neurons in a circuit that is involved in learning about a stimulus or a contingency. A key limitation of current methods to analyze neural spiking data is the need to collapse neural activity over time or trials, which may cause the loss of information pertinent to understanding the function of a neuron or circuit. We introduce a new method that can determine not only the trial-to-trial dynamics that accompany the learning of a contingency by a neuron, but also the latency of this learning with respect to the onset of a conditioned stimulus. The backbone of the method is a separable two-dimensional (2D) random field (RF) model of neural spike rasters, in which the joint conditional intensity function of a neuron over time and trials depends on two latent Markovian state sequences that evolve separately but in parallel. Classical tools to estimate state-space models cannot be applied readily to our 2D separable RF model. We develop efficient statistical and computational tools to estimate the parameters of the separable 2D RF model. We apply these to data collected from neurons in the prefrontal cortex in an experiment designed to characterize the neural underpinnings of the associative learning of fear in mice. Overall, the separable 2D RF model provides a detailed, interpretable characterization of the dynamics of neural spiking that accompany the learning of a contingency.
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Affiliation(s)
- Yingzhuo Zhang
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, U.S.A.
| | | | - Stephen A Allsop
- Department of Brain and Cognitive Sciences and Picower Institute for Learning and Memory, Cambridge, MA 02139, U.S.A.
| | - Kay M Tye
- Department of Brain and Cognitive Sciences and Picower Institute for Learning and Memory, Cambridge, MA 02139, U.S.A.
| | - Demba Ba
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, U.S.A.
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28
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Beyeler A, Chang CJ, Silvestre M, Lévêque C, Namburi P, Wildes CP, Tye KM. Organization of Valence-Encoding and Projection-Defined Neurons in the Basolateral Amygdala. Cell Rep 2018; 22:905-918. [PMID: 29386133 PMCID: PMC5891824 DOI: 10.1016/j.celrep.2017.12.097] [Citation(s) in RCA: 148] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 10/30/2017] [Accepted: 12/26/2017] [Indexed: 01/03/2023] Open
Abstract
The basolateral amygdala (BLA) mediates associative learning for both
fear and reward. Accumulating evidence supports the notion that different BLA
projections distinctly alter motivated behavior, including projections to the
nucleus accumbens (NAc), medial aspect of the central amygdala (CeM), and
ventral hippocampus (vHPC). Although there is consensus regarding the existence
of distinct subsets of BLA neurons encoding positive or negative valence,
controversy remains regarding the anatomical arrangement of these populations.
First, we map the location of more than 1,000 neurons distributed across the BLA
and recorded during a Pavlovian discrimination task. Next, we determine the
location of projection-defined neurons labeled with retrograde tracers and use
CLARITY to reveal the axonal path in 3-dimensional space. Finally, we examine
the local influence of each projection-defined populations within the BLA.
Understanding the functional and topographical organization of circuits
underlying valence assignment could reveal fundamental principles about
emotional processing.
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Affiliation(s)
- Anna Beyeler
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Neurocentre Magendie, INSERM, U1215, University of Bordeaux, 146 rue Léo Saignat, 33077 Bordeaux Cedex, France.
| | - Chia-Jung Chang
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Margaux Silvestre
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Clémentine Lévêque
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Praneeth Namburi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Craig P Wildes
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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29
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Burgos-Robles A, Kimchi EY, Izadmehr EM, Porzenheim MJ, Ramos-Guasp WA, Nieh EH, Felix-Ortiz AC, Namburi P, Leppla CA, Presbrey KN, Anandalingam KK, Pagan-Rivera PA, Anahtar M, Beyeler A, Tye KM. Amygdala inputs to prefrontal cortex guide behavior amid conflicting cues of reward and punishment. Nat Neurosci 2017; 20:824-835. [PMID: 28436980 PMCID: PMC5448704 DOI: 10.1038/nn.4553] [Citation(s) in RCA: 180] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Accepted: 03/22/2017] [Indexed: 12/13/2022]
Abstract
Orchestrating appropriate behavioral responses in the face of competing signals that predict either rewards or threats in the environment is crucial for survival. The basolateral nucleus of the amygdala (BLA) and prelimbic (PL) medial prefrontal cortex have been implicated in reward-seeking and fear-related responses, but how information flows between these reciprocally connected structures to coordinate behavior is unknown. We recorded neuronal activity from the BLA and PL while rats performed a task wherein competing shock- and sucrose-predictive cues were simultaneously presented. The correlated firing primarily displayed a BLA→PL directionality during the shock-associated cue. Furthermore, BLA neurons optogenetically identified as projecting to PL more accurately predicted behavioral responses during competition than unidentified BLA neurons. Finally photostimulation of the BLA→PL projection increased freezing, whereas both chemogenetic and optogenetic inhibition reduced freezing. Therefore, the BLA→PL circuit is critical in governing the selection of behavioral responses in the face of competing signals.
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Affiliation(s)
- Anthony Burgos-Robles
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Eyal Y Kimchi
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Ehsan M Izadmehr
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mary Jane Porzenheim
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - William A Ramos-Guasp
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Edward H Nieh
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Ada C Felix-Ortiz
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Praneeth Namburi
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Christopher A Leppla
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kara N Presbrey
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kavitha K Anandalingam
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Pablo A Pagan-Rivera
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Melodi Anahtar
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Anna Beyeler
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kay M Tye
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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31
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Matthews GA, Nieh EH, Vander Weele CM, Halbert SA, Pradhan RV, Yosafat AS, Glober GF, Izadmehr EM, Thomas RE, Lacy GD, Wildes CP, Ungless MA, Tye KM. Dorsal Raphe Dopamine Neurons Represent the Experience of Social Isolation. Cell 2016; 164:617-31. [PMID: 26871628 PMCID: PMC4752823 DOI: 10.1016/j.cell.2015.12.040] [Citation(s) in RCA: 235] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2015] [Revised: 09/28/2015] [Accepted: 12/21/2015] [Indexed: 01/12/2023]
Abstract
The motivation to seek social contact may arise from either positive or negative emotional states, as social interaction can be rewarding and social isolation can be aversive. While ventral tegmental area (VTA) dopamine (DA) neurons may mediate social reward, a cellular substrate for the negative affective state of loneliness has remained elusive. Here, we identify a functional role for DA neurons in the dorsal raphe nucleus (DRN), in which we observe synaptic changes following acute social isolation. DRN DA neurons show increased activity upon social contact following isolation, revealed by in vivo calcium imaging. Optogenetic activation of DRN DA neurons increases social preference but causes place avoidance. Furthermore, these neurons are necessary for promoting rebound sociability following an acute period of isolation. Finally, the degree to which these neurons modulate behavior is predicted by social rank, together supporting a role for DRN dopamine neurons in mediating a loneliness-like state. PAPERCLIP.
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Affiliation(s)
- Gillian A Matthews
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Medical Research Council Clinical Sciences Centre, Imperial College London, Hammersmith Hospital, Du Cane Road, W12 0NN London, UK
| | - Edward H Nieh
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Caitlin M Vander Weele
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Sarah A Halbert
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Roma V Pradhan
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ariella S Yosafat
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gordon F Glober
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ehsan M Izadmehr
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Rain E Thomas
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gabrielle D Lacy
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Craig P Wildes
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mark A Ungless
- Medical Research Council Clinical Sciences Centre, Imperial College London, Hammersmith Hospital, Du Cane Road, W12 0NN London, UK.
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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32
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Namburi P, Al-Hasani R, Calhoon GG, Bruchas MR, Tye KM. Architectural Representation of Valence in the Limbic System. Neuropsychopharmacology 2016; 41:1697-715. [PMID: 26647973 PMCID: PMC4869057 DOI: 10.1038/npp.2015.358] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2015] [Revised: 12/04/2015] [Accepted: 12/05/2015] [Indexed: 11/08/2022]
Abstract
In order to thrive, animals must be able to recognize aversive and appetitive stimuli within the environment and subsequently initiate appropriate behavioral responses. This assignment of positive or negative valence to a stimulus is a key feature of emotional processing, the neural substrates of which have been a topic of study for several decades. Until recently, the result of this work has been the identification of specific brain regions, such as the basolateral amygdala (BLA) and nucleus accumbens (NAc), as important to valence encoding. The advent of modern tools in neuroscience has allowed further dissection of these regions to identify specific populations of neurons signaling the valence of environmental stimuli. In this review, we focus upon recent work examining the mechanisms of valence encoding, and provide a model for the systematic investigation of valence within anatomically-, genetically-, and functionally defined populations of neurons.
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Affiliation(s)
- Praneeth Namburi
- Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Neuroscience Graduate Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ream Al-Hasani
- Division of Basic Research, Department of Anesthesiology, Washington University School of Medicine, St Louis, MO, USA
- Washington University Pain Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
| | - Gwendolyn G Calhoon
- Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael R Bruchas
- Division of Basic Research, Department of Anesthesiology, Washington University School of Medicine, St Louis, MO, USA
- Washington University Pain Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St Louis, MO, USA
| | - Kay M Tye
- Department of Brain and Cognitive Sciences, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
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Beyeler A, Namburi P, Glober GF, Simonnet C, Calhoon GG, Conyers GF, Luck R, Wildes CP, Tye KM. Divergent Routing of Positive and Negative Information from the Amygdala during Memory Retrieval. Neuron 2016; 90:348-361. [PMID: 27041499 DOI: 10.1016/j.neuron.2016.03.004] [Citation(s) in RCA: 248] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Revised: 01/08/2016] [Accepted: 02/16/2016] [Indexed: 12/30/2022]
Abstract
Although the basolateral amygdala (BLA) is known to play a critical role in the formation of memories of both positive and negative valence, the coding and routing of valence-related information is poorly understood. Here, we recorded BLA neurons during the retrieval of associative memories and used optogenetic-mediated phototagging to identify populations of neurons that synapse in the nucleus accumbens (NAc), the central amygdala (CeA), or ventral hippocampus (vHPC). We found that despite heterogeneous neural responses within each population, the proportions of BLA-NAc neurons excited by reward predictive cues and of BLA-CeA neurons excited by aversion predictive cues were higher than within the entire BLA. Although the BLA-vHPC projection is known to drive behaviors of innate negative valence, these neurons did not preferentially code for learned negative valence. Together, these findings suggest that valence encoding in the BLA is at least partially mediated via divergent activity of anatomically defined neural populations.
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Affiliation(s)
- Anna Beyeler
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Praneeth Namburi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Gordon F Glober
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Clémence Simonnet
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Gwendolyn G Calhoon
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Garrett F Conyers
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Robert Luck
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Craig P Wildes
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
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34
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Adamantidis A, Arber S, Bains JS, Bamberg E, Bonci A, Buzsáki G, Cardin JA, Costa RM, Dan Y, Goda Y, Graybiel AM, Häusser M, Hegemann P, Huguenard JR, Insel TR, Janak PH, Johnston D, Josselyn SA, Koch C, Kreitzer AC, Lüscher C, Malenka RC, Miesenböck G, Nagel G, Roska B, Schnitzer MJ, Shenoy KV, Soltesz I, Sternson SM, Tsien RW, Tsien RY, Turrigiano GG, Tye KM, Wilson RI. Optogenetics: 10 years after ChR2 in neurons--views from the community. Nat Neurosci 2015; 18:1202-12. [PMID: 26308981 DOI: 10.1038/nn.4106] [Citation(s) in RCA: 88] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Antoine Adamantidis
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montréal, Canada, and the Department of Neurology, Inselspital University Hospital, University of Bern, Bern, Switzerland
| | - Silvia Arber
- Biozentrum, Department of Cell Biology, University of Basel, Basel, Switzerland, and the Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Jaideep S Bains
- Department of Physiology and Pharmacology, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Ernst Bamberg
- Max Planck Institute of Biophysics, Frankfurt am Main, Germany
| | - Antonello Bonci
- Intramural Research Program, Synaptic Plasticity Section, National Institute on Drug Abuse, Baltimore, Maryland, USA, the Solomon H. Snyder Neuroscience Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA, and in the Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - György Buzsáki
- The Neuroscience Institute, School of Medicine and Center for Neural Science, New York University, New York, New York, USA
| | - Jessica A Cardin
- Department of Neurobiology, Yale University School of Medicine, New Haven, Connecticut, USA, and at the Kavli Institute of Neuroscience, Yale University, New Haven, Connecticut, USA
| | - Rui M Costa
- Champalimaud Neuroscience Programme, Champalimaud Center for the Unknown, Lisbon, Portugal
| | - Yang Dan
- Division of Neurobiology, Department of Molecular and Cell Biology, Helen Wills Neuroscience Institute, Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, California, USA
| | - Yukiko Goda
- RIKEN Brain Science Institute, Wako-shi, Saitama, Japan
| | - Ann M Graybiel
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Michael Häusser
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, United Kingdom
| | - Peter Hegemann
- Institut für Biologie/Experimentelle Biophysik, Humboldt Universität zu Berlin, Berlin, Germany
| | - John R Huguenard
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Thomas R Insel
- National Institute of Mental Health, Bethesda, Maryland, USA
| | - Patricia H Janak
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, Maryland, USA, and the Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland, USA
| | - Daniel Johnston
- Department of Neuroscience and Center for Learning and Memory, University of Texas at Austin, Austin, Texas, USA
| | - Sheena A Josselyn
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Peter Gilgan Centre for Research and Learning, Toronto, Ontario, Canada, and the Departments of Psychology and Physiology and Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Christof Koch
- Allen Institute for Brain Science, Seattle, Washington, USA
| | - Anatol C Kreitzer
- The Gladstone Institutes, San Francisco, California, USA, and the Departments of Neurology and Physiology, University of California, San Francisco, San Francisco, California, USA
| | - Christian Lüscher
- Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland, and the Service of Neurology, Department of Clinical Neurosciences, University Hospital of Geneva, Geneva, Switzerland
| | - Robert C Malenka
- Nancy Pritzker Laboratory, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, California, USA
| | - Gero Miesenböck
- Centre for Neural Circuits and Behaviour, University of Oxford, Tinsley Building, Mansfield Road, Oxford, UK
| | - Georg Nagel
- Institute for Molecular Plant Physiology and Biophysics, Biocenter, Julius-Maximilians-University of Würzburg, Würzburg, Germany
| | - Botond Roska
- Neural Circuit Laboratories, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. Department of Ophthalmology, University of Basel, Basel, Switzerland
| | - Mark J Schnitzer
- James H. Clark Center for Biomedical Engineering and Sciences, Stanford University, Stanford, California, USA, the Howard Hughes Medical Institute, Stanford University, Stanford, California, USA, and the CNC Program, Stanford University, Stanford, California, USA
| | - Krishna V Shenoy
- Departments of Electrical Engineering, Bioengineering and Neurobiology, the Neurosciences and Bio-X Programs, the Stanford Neurosciences Institute and the Howard Hughes Medical Institute, Stanford University, Stanford, California, USA
| | - Ivan Soltesz
- Department of Neurosurgery, Stanford University, Stanford, California, USA
| | - Scott M Sternson
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
| | - Richard W Tsien
- Department of Neuroscience and Physiology, Neuroscience Institute, New York University Langone Medical Center, New York, New York, USA
| | - Roger Y Tsien
- Department of Pharmacology, Howard Hughes Medical Institute, Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California, USA
| | - Gina G Turrigiano
- Department of Biology and Center for Behavioral Genomics, Brandeis University, Waltham, Massachusetts, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, Boston, Massachusetts, USA
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Abstract
Although anxiety disorders represent a major societal problem demanding new therapeutic targets, these efforts have languished in the absence of a mechanistic understanding of this subjective emotional state. While it is impossible to know with certainty the subjective experience of a rodent, rodent models hold promise in dissecting well-conserved limbic circuits. The application of modern approaches in neuroscience has already begun to unmask the neural circuit intricacies underlying anxiety by allowing direct examination of hypotheses drawn from existing psychological concepts. This information points toward an updated conceptual model for what neural circuit perturbations could give rise to pathological anxiety and thereby provides a roadmap for future therapeutic development.
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Affiliation(s)
- Gwendolyn G Calhoon
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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Felix-Ortiz AC, Burgos-Robles A, Bhagat ND, Leppla CA, Tye KM. Bidirectional modulation of anxiety-related and social behaviors by amygdala projections to the medial prefrontal cortex. Neuroscience 2015. [PMID: 26204817 DOI: 10.1016/j.neuroscience.2015.07.041] [Citation(s) in RCA: 249] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The basolateral amygdala (BLA) and the medial prefrontal cortex (mPFC) modulate anxiety and social behaviors. It remains to be elucidated, however, whether direct projections from the BLA to the mPFC play a functional role in these behaviors. We used optogenetic approaches in behaving mice to either activate or inhibit BLA inputs to the mPFC during behavioral assays that assess anxiety-like behavior and social interaction. Channelrhodopsin-2 (ChR2)-mediated activation of BLA inputs to the mPFC produced anxiogenic effects in the elevated plus maze and open field test, whereas halorhodopsin (NpHR)-mediated inhibition produced anxiolytic effects. Furthermore, activation of the BLA-mPFC pathway reduced social interaction in the resident-intruder test, whereas inhibition facilitated social interaction. These results establish a causal relationship between activity in the BLA-mPFC pathway and the bidirectional modulation of anxiety-related and social behaviors.
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Affiliation(s)
- A C Felix-Ortiz
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - A Burgos-Robles
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - N D Bhagat
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Program in Behavioral Neuroscience, Northeastern University, Boston, MA 02115, USA.
| | - C A Leppla
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - K M Tye
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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37
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Namburi P, Beyeler A, Yorozu S, Calhoon GG, Halbert SA, Wichmann R, Holden SS, Mertens KL, Anahtar M, Felix-Ortiz AC, Wickersham IR, Gray JM, Tye KM. A circuit mechanism for differentiating positive and negative associations. Nature 2015; 520:675-8. [PMID: 25925480 PMCID: PMC4418228 DOI: 10.1038/nature14366] [Citation(s) in RCA: 358] [Impact Index Per Article: 39.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2014] [Accepted: 03/03/2015] [Indexed: 12/18/2022]
Abstract
The ability to differentiate stimuli predicting positive or negative outcomes is critical for survival, and perturbations of emotional processing underlie many psychiatric disease states. Synaptic plasticity in the basolateral amygdala complex (BLA) mediates the acquisition of associative memories, both positive and negative. Different populations of BLA neurons may encode fearful or rewarding associations, but the identifying features of these populations and the synaptic mechanisms of differentiating positive and negative emotional valence have remained unknown. Here we show that BLA neurons projecting to the nucleus accumbens (NAc projectors) or the centromedial amygdala (CeM projectors) undergo opposing synaptic changes following fear or reward conditioning. We find that photostimulation of NAc projectors supports positive reinforcement while photostimulation of CeM projectors mediates negative reinforcement. Photoinhibition of CeM projectors impairs fear conditioning and enhances reward conditioning. We characterize these functionally distinct neuronal populations by comparing their electrophysiological, morphological and genetic features. Overall, we provide a mechanistic explanation for the representation of positive and negative associations within the amygdala.
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Affiliation(s)
- Praneeth Namburi
- 1] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [2] Neuroscience Graduate Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Anna Beyeler
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Suzuko Yorozu
- Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, NRB 356, Boston, Massachusetts 02115, USA
| | - Gwendolyn G Calhoon
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Sarah A Halbert
- 1] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [2] Undergraduate Program in Neuroscience, Wellesley College, Wellesley, Massachusetts 02481, USA
| | - Romy Wichmann
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Stephanie S Holden
- 1] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [2] Undergraduate Program in Neuroscience, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Kim L Mertens
- 1] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [2] Master's Program in Biomedical Sciences, University of Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Melodi Anahtar
- 1] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [2] Undergraduate Program in Neuroscience, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Ada C Felix-Ortiz
- 1] The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [2] Neuroscience Graduate Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Ian R Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Jesse M Gray
- Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, NRB 356, Boston, Massachusetts 02115, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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38
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Nieh EH, Matthews GA, Allsop SA, Presbrey KN, Leppla CA, Wichmann R, Neve R, Wildes CP, Tye KM. Decoding neural circuits that control compulsive sucrose seeking. Cell 2015; 160:528-41. [PMID: 25635460 DOI: 10.1016/j.cell.2015.01.003] [Citation(s) in RCA: 263] [Impact Index Per Article: 29.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2014] [Revised: 11/02/2014] [Accepted: 12/23/2014] [Indexed: 11/19/2022]
Abstract
The lateral hypothalamic (LH) projection to the ventral tegmental area (VTA) has been linked to reward processing, but the computations within the LH-VTA loop that give rise to specific aspects of behavior have been difficult to isolate. We show that LH-VTA neurons encode the learned action of seeking a reward, independent of reward availability. In contrast, LH neurons downstream of VTA encode reward-predictive cues and unexpected reward omission. We show that inhibiting the LH-VTA pathway reduces "compulsive" sucrose seeking but not food consumption in hungry mice. We reveal that the LH sends excitatory and inhibitory input onto VTA dopamine (DA) and GABA neurons, and that the GABAergic projection drives feeding-related behavior. Our study overlays information about the type, function, and connectivity of LH neurons and identifies a neural circuit that selectively controls compulsive sugar consumption, without preventing feeding necessary for survival, providing a potential target for therapeutic interventions for compulsive-overeating disorder.
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Affiliation(s)
- Edward H Nieh
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gillian A Matthews
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Stephen A Allsop
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kara N Presbrey
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Christopher A Leppla
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Romy Wichmann
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Rachael Neve
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Craig P Wildes
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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39
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Abstract
Theoretically, harnessing the brain's own endogenous plasticity mechanisms could serve to alter both internal states and external behavior in a therapeutic manner.
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Affiliation(s)
- Kay M Tye
- Picower Institute for Learning and Memory, Brain & Cognitive Sciences Department, MIT, Cambridge, MA 02139, USA.
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40
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Sidor MM, Davidson TJ, Tye KM, Warden MR, Diesseroth K, McClung CA. In vivo optogenetic stimulation of the rodent central nervous system. J Vis Exp 2015:51483. [PMID: 25651158 DOI: 10.3791/51483] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
The ability to probe defined neural circuits in awake, freely-moving animals with cell-type specificity, spatial precision, and high temporal resolution has been a long sought tool for neuroscientists in the systems-level search for the neural circuitry governing complex behavioral states. Optogenetics is a cutting-edge tool that is revolutionizing the field of neuroscience and represents one of the first systematic approaches to enable causal testing regarding the relation between neural signaling events and behavior. By combining optical and genetic approaches, neural signaling can be bi-directionally controlled through expression of light-sensitive ion channels (opsins) in mammalian cells. The current protocol describes delivery of specific wavelengths of light to opsin-expressing cells in deep brain structures of awake, freely-moving rodents for neural circuit modulation. Theoretical principles of light transmission as an experimental consideration are discussed in the context of performing in vivo optogenetic stimulation. The protocol details the design and construction of both simple and complex laser configurations and describes tethering strategies to permit simultaneous stimulation of multiple animals for high-throughput behavioral testing.
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Affiliation(s)
- Michelle M Sidor
- Department of Psychiatry, University of Pittsburgh Medical Center;
| | | | - Kay M Tye
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of Technology
| | | | - Karl Diesseroth
- Department of Bioengineering, Stanford University; Department of Psychiatry and Behavioral Sciences, Stanford University
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41
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Haws ME, Jaramillo TC, Espinosa F, Widman AJ, Stuber GD, Sparta DR, Tye KM, Russo SJ, Parada LF, Stavarache M, Kaplitt M, Bonci A, Powell CM. PTEN knockdown alters dendritic spine/protrusion morphology, not density. J Comp Neurol 2014; 522:1171-90. [PMID: 24264880 DOI: 10.1002/cne.23488] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2013] [Revised: 10/02/2013] [Accepted: 10/03/2013] [Indexed: 12/12/2022]
Abstract
Mutations in phosphatase and tensin homolog deleted on chromosome 10 (PTEN) are implicated in neuropsychiatric disorders including autism. Previous studies report that PTEN knockdown in neurons in vivo leads to increased spine density and synaptic activity. To better characterize synaptic changes in neurons lacking PTEN, we examined the effects of shRNA knockdown of PTEN in basolateral amygdala neurons on synaptic spine density and morphology by using fluorescent dye confocal imaging. Contrary to previous studies in the dentate gyrus, we find that knockdown of PTEN in basolateral amygdala leads to a significant decrease in total spine density in distal dendrites. Curiously, this decreased spine density is associated with increased miniature excitatory postsynaptic current frequency and amplitude, suggesting an increase in number and function of mature spines. These seemingly contradictory findings were reconciled by spine morphology analysis demonstrating increased mushroom spine density and size with correspondingly decreased thin protrusion density at more distal segments. The same analysis of PTEN conditional deletion in the dentate gyrus demonstrated that loss of PTEN does not significantly alter total density of dendritic protrusions in the dentate gyrus, but does decrease thin protrusion density and increases density of more mature mushroom spines. These findings suggest that, contrary to previous reports, PTEN knockdown may not induce de novo spinogenesis, but instead may increase synaptic activity by inducing morphological and functional maturation of spines. Furthermore, behavioral analysis of basolateral amygdala PTEN knockdown suggests that these changes limited only to the basolateral amygdala complex may not be sufficient to induce increased anxiety-related behaviors.
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Affiliation(s)
- Michael E Haws
- Department of Neurology & Neurotherapeutics, The University of Texas Southwestern Medical Center, Dallas, Texas, 75390-8813; Neuroscience Graduate Program, The University of Texas Southwestern Medical Center, Dallas, Texas, 75390-8813
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42
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Gunaydin LA, Grosenick L, Finkelstein JC, Kauvar IV, Fenno LE, Adhikari A, Lammel S, Mirzabekov JJ, Airan RD, Zalocusky KA, Tye KM, Anikeeva P, Malenka RC, Deisseroth K. Natural neural projection dynamics underlying social behavior. Cell 2014; 157:1535-51. [PMID: 24949967 DOI: 10.1016/j.cell.2014.05.017] [Citation(s) in RCA: 871] [Impact Index Per Article: 87.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2014] [Revised: 04/30/2014] [Accepted: 05/12/2014] [Indexed: 01/11/2023]
Abstract
Social interaction is a complex behavior essential for many species and is impaired in major neuropsychiatric disorders. Pharmacological studies have implicated certain neurotransmitter systems in social behavior, but circuit-level understanding of endogenous neural activity during social interaction is lacking. We therefore developed and applied a new methodology, termed fiber photometry, to optically record natural neural activity in genetically and connectivity-defined projections to elucidate the real-time role of specified pathways in mammalian behavior. Fiber photometry revealed that activity dynamics of a ventral tegmental area (VTA)-to-nucleus accumbens (NAc) projection could encode and predict key features of social, but not novel object, interaction. Consistent with this observation, optogenetic control of cells specifically contributing to this projection was sufficient to modulate social behavior, which was mediated by type 1 dopamine receptor signaling downstream in the NAc. Direct observation of deep projection-specific activity in this way captures a fundamental and previously inaccessible dimension of mammalian circuit dynamics.
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Affiliation(s)
- Lisa A Gunaydin
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Logan Grosenick
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Neuroscience Program, Stanford University, Stanford, CA 94305, USA
| | - Joel C Finkelstein
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Isaac V Kauvar
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Lief E Fenno
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Neuroscience Program, Stanford University, Stanford, CA 94305, USA
| | - Avishek Adhikari
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Stephan Lammel
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Julie J Mirzabekov
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Raag D Airan
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Kelly A Zalocusky
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Neuroscience Program, Stanford University, Stanford, CA 94305, USA
| | - Kay M Tye
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Polina Anikeeva
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Robert C Malenka
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
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43
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Chuong AS, Miri ML, Busskamp V, Matthews GAC, Acker LC, Sørensen AT, Young A, Klapoetke NC, Henninger MA, Kodandaramaiah SB, Ogawa M, Ramanlal SB, Bandler RC, Allen BD, Forest CR, Chow BY, Han X, Lin Y, Tye KM, Roska B, Cardin JA, Boyden ES. Noninvasive optical inhibition with a red-shifted microbial rhodopsin. Nat Neurosci 2014; 17:1123-9. [PMID: 24997763 PMCID: PMC4184214 DOI: 10.1038/nn.3752] [Citation(s) in RCA: 346] [Impact Index Per Article: 34.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2014] [Accepted: 06/01/2014] [Indexed: 12/11/2022]
Abstract
Optogenetic inhibition of the electrical activity of neurons enables the causal assessment of their contributions to brain functions. Red light penetrates deeper into tissue than other visible wavelengths. We present a red-shifted cruxhalorhodopsin, Jaws, derived from Haloarcula (Halobacterium) salinarum (strain Shark) and engineered to result in red light-induced photocurrents three times those of earlier silencers. Jaws exhibits robust inhibition of sensory-evoked neural activity in the cortex and results in strong light responses when used in retinas of retinitis pigmentosa model mice. We also demonstrate that Jaws can noninvasively mediate transcranial optical inhibition of neurons deep in the brains of awake mice. The noninvasive optogenetic inhibition opened up by Jaws enables a variety of important neuroscience experiments and offers a powerful general-use chloride pump for basic and applied neuroscience.
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Affiliation(s)
- Amy S Chuong
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mitra L Miri
- 1] Department of Neurobiology, Yale School of Medicine, Yale University, New Haven, Connecticut, USA. [2]
| | - Volker Busskamp
- 1] Neural Circuit Laboratories, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. [2] Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA. [3]
| | - Gillian A C Matthews
- 1] Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2]
| | - Leah C Acker
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [4]
| | - Andreas T Sørensen
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Andrew Young
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Nathan C Klapoetke
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mike A Henninger
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Suhasa B Kodandaramaiah
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [4] George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Masaaki Ogawa
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Shreshtha B Ramanlal
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Rachel C Bandler
- Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Brian D Allen
- Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Brian Y Chow
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Yingxi Lin
- McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kay M Tye
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Botond Roska
- Neural Circuit Laboratories, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Jessica A Cardin
- 1] Department of Neurobiology, Yale School of Medicine, Yale University, New Haven, Connecticut, USA. [2] Kavli Institute for Neuroscience, Yale University, New Haven, Connecticut, USA
| | - Edward S Boyden
- 1] Media Lab, Department of Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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44
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Allsop SA, Vander Weele CM, Wichmann R, Tye KM. Optogenetic insights on the relationship between anxiety-related behaviors and social deficits. Front Behav Neurosci 2014; 8:241. [PMID: 25076878 PMCID: PMC4099964 DOI: 10.3389/fnbeh.2014.00241] [Citation(s) in RCA: 104] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2014] [Accepted: 06/20/2014] [Indexed: 11/25/2022] Open
Abstract
Many psychiatric illnesses are characterized by deficits in the social domain. For example, there is a high rate of co-morbidity between autism spectrum disorders and anxiety disorders. However, the common neural circuit mechanisms by which social deficits and other psychiatric disease states, such as anxiety, are co-expressed remains unclear. Here, we review optogenetic investigations of neural circuits in animal models of anxiety-related behaviors and social behaviors and discuss the important role of the amygdala in mediating aspects of these behaviors. In particular, we focus on recent evidence that projections from the basolateral amygdala (BLA) to the ventral hippocampus (vHPC) modulate anxiety-related behaviors and also alter social interaction. Understanding how this circuit influences both social behavior and anxiety may provide a mechanistic explanation for the pathogenesis of social anxiety disorder, as well as the prevalence of patients co-diagnosed with autism spectrum disorders and anxiety disorders. Furthermore, elucidating how circuits that modulate social behavior also mediate other complex emotional states will lead to a better understanding of the underlying mechanisms by which social deficits are expressed in psychiatric disease.
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Affiliation(s)
- Stephen A. Allsop
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of TechnologyCambridge, MA, USA
- Harvard Medical School, Harvard UniversityBoston, MA, USA
| | - Caitlin M. Vander Weele
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of TechnologyCambridge, MA, USA
| | - Romy Wichmann
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of TechnologyCambridge, MA, USA
| | - Kay M. Tye
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of TechnologyCambridge, MA, USA
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45
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Beyeler A, Eckhardt CA, Tye KM. Deciphering Memory Function with Optogenetics. Progress in Molecular Biology and Translational Science 2014; 122:341-90. [DOI: 10.1016/b978-0-12-420170-5.00012-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
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46
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Abstract
The basolateral amygdala (BLA) and ventral hippocampus (vHPC) have both been implicated in mediating anxiety-related behaviors, but the functional contribution of BLA inputs to the vHPC has never been directly investigated. Here we show that activation of BLA-vHPC synapses acutely and robustly increased anxiety-related behaviors, while inhibition of BLA-vHPC synapses decreased anxiety-related behaviors. We combined optogenetic approaches with in vivo pharmacological manipulations and ex vivo whole-cell patch-clamp recordings to dissect the local circuit mechanisms, demonstrating that activation of BLA terminals in the vHPC provided monosynaptic, glutamatergic inputs to vHPC pyramidal neurons. Furthermore, BLA inputs exerted polysynaptic, inhibitory effects mediated by local interneurons in the vHPC that may serve to balance the circuit locally. These data establish a role for BLA-vHPC synapses in bidirectionally controlling anxiety-related behaviors in an immediate, yet reversible, manner and a model for the local circuit mechanism of BLA inputs in the vHPC.
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Affiliation(s)
- Ada C Felix-Ortiz
- The Picower Institute for Learning and Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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47
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Lammel S, Tye KM, Warden MR. Progress in understanding mood disorders: optogenetic dissection of neural circuits. Genes Brain Behav 2013; 13:38-51. [PMID: 23682971 DOI: 10.1111/gbb.12049] [Citation(s) in RCA: 81] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2013] [Revised: 04/22/2013] [Accepted: 05/14/2013] [Indexed: 12/13/2022]
Abstract
Major depression is characterized by a cluster of symptoms that includes hopelessness, low mood, feelings of worthlessness and inability to experience pleasure. The lifetime prevalence of major depression approaches 20%, yet current treatments are often inadequate both because of associated side effects and because they are ineffective for many people. In basic research, animal models are often used to study depression. Typically, experimental animals are exposed to acute or chronic stress to generate a variety of depression-like symptoms. Despite its clinical importance, very little is known about the cellular and neural circuits that mediate these symptoms. Recent advances in circuit-targeted approaches have provided new opportunities to study the neuropathology of mood disorders such as depression and anxiety. We review recent progress and highlight some studies that have begun tracing a functional neuronal circuit diagram that may prove essential in establishing novel treatment strategies in mood disorders. First, we shed light on the complexity of mesocorticolimbic dopamine (DA) responses to stress by discussing two recent studies reporting that optogenetic activation of midbrain DA neurons can induce or reverse depression-related behaviors. Second, we describe the role of the lateral habenula circuitry in the pathophysiology of depression. Finally, we discuss how the prefrontal cortex controls limbic and neuromodulatory circuits in mood disorders.
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Affiliation(s)
- S Lammel
- Nancy Pritzker Laboratory, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
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48
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Nieh EH, Kim SY, Namburi P, Tye KM. Optogenetic dissection of neural circuits underlying emotional valence and motivated behaviors. Brain Res 2013; 1511:73-92. [PMID: 23142759 PMCID: PMC4099056 DOI: 10.1016/j.brainres.2012.11.001] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2012] [Revised: 11/01/2012] [Accepted: 11/02/2012] [Indexed: 12/26/2022]
Abstract
The neural circuits underlying emotional valence and motivated behaviors are several synapses away from both defined sensory inputs and quantifiable motor outputs. Electrophysiology has provided us with a suitable means for observing neural activity during behavior, but methods for controlling activity for the purpose of studying motivated behaviors have been inadequate: electrical stimulation lacks cellular specificity and pharmacological manipulation lacks temporal resolution. The recent emergence of optogenetic tools provides a new means for establishing causal relationships between neural activity and behavior. Optogenetics, the use of genetically-encodable light-activated proteins, permits the modulation of specific neural circuit elements with millisecond precision. The ability to control individual cell types, and even projections between distal regions, allows us to investigate functional connectivity in a causal manner. The greatest consequence of controlling neural activity with finer precision has been the characterization of individual neural circuits within anatomical brain regions as defined functional units. Within the mesolimbic dopamine system, optogenetics has helped separate subsets of dopamine neurons with distinct functions for reward, aversion and salience processing, elucidated GABA neuronal effects on behavior, and characterized connectivity with forebrain and cortical structures. Within the striatum, optogenetics has confirmed the opposing relationship between direct and indirect pathway medium spiny neurons (MSNs), in addition to characterizing the inhibition of MSNs by cholinergic interneurons. Within the hypothalamus, optogenetics has helped overcome the heterogeneity in neuronal cell-type and revealed distinct circuits mediating aggression and feeding. Within the amygdala, optogenetics has allowed the study of intra-amygdala microcircuitry as well as interconnections with distal regions involved in fear and anxiety. In this review, we will present the body of optogenetic studies that has significantly enhanced our understanding of emotional valence and motivated behaviors. This article is part of a Special Issue entitled Optogenetics (7th BRES).
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Affiliation(s)
- Edward H. Nieh
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sung-Yon Kim
- Department of Bioengineering, Neurosciences Program, Stanford University, Stanford, CA, USA
| | - Praneeth Namburi
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kay M. Tye
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
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49
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Tye KM, Mirzabekov JJ, Warden MR, Ferenczi EA, Tsai HC, Finkelstein J, Kim SY, Adhikari A, Thompson KR, Andalman AS, Gunaydin LA, Witten IB, Deisseroth K. Dopamine neurons modulate neural encoding and expression of depression-related behaviour. Nature 2012; 493:537-541. [PMID: 23235822 PMCID: PMC4160519 DOI: 10.1038/nature11740] [Citation(s) in RCA: 707] [Impact Index Per Article: 58.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2012] [Accepted: 10/31/2012] [Indexed: 02/08/2023]
Abstract
Major depression is characterized by diverse debilitating symptoms that include hopelessness and anhedonia. Dopamine neurons involved in reward and motivation are among many neural populations that have been hypothesized to be relevant, and certain antidepressant treatments, including medications and brain stimulation therapies, can influence the complex dopamine system. Until now it has not been possible to test this hypothesis directly, even in animal models, as existing therapeutic interventions are unable to specifically target dopamine neurons. Here we investigated directly the causal contributions of defined dopamine neurons to multidimensional depression-like phenotypes induced by chronic mild stress, by integrating behavioural, pharmacological, optogenetic and electrophysiological methods in freely moving rodents. We found that bidirectional control (inhibition or excitation) of specified midbrain dopamine neurons immediately and bidirectionally modulates (induces or relieves) multiple independent depression symptoms caused by chronic stress. By probing the circuit implementation of these effects, we observed that optogenetic recruitment of these dopamine neurons potently alters the neural encoding of depression-related behaviours in the downstream nucleus accumbens of freely moving rodents, suggesting that processes affecting depression symptoms may involve alterations in the neural encoding of action in limbic circuitry.
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Affiliation(s)
- Kay M Tye
- Picower Institute for Learning and Memory, Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.,Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Julie J Mirzabekov
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Melissa R Warden
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Emily A Ferenczi
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA.,Neurosciences Program, Stanford University, Stanford California 94305, USA
| | - Hsing-Chen Tsai
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA.,Neurosciences Program, Stanford University, Stanford California 94305, USA
| | - Joel Finkelstein
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Sung-Yon Kim
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA.,Neurosciences Program, Stanford University, Stanford California 94305, USA
| | - Avishek Adhikari
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Kimberly R Thompson
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Aaron S Andalman
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Lisa A Gunaydin
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Ilana B Witten
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, California 94305, USA.,Neurosciences Program, Stanford University, Stanford California 94305, USA.,Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94305, USA.,Howard Hughes Medical Institute, Stanford University, Stanford California 94305, USA.,CNC Program, Stanford University, Stanford, California 94305, USA
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50
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Tan KR, Yvon C, Turiault M, Mirzabekov JJ, Doehner J, Labouèbe G, Deisseroth K, Tye KM, Lüscher C. GABA neurons of the VTA drive conditioned place aversion. Neuron 2012; 73:1173-83. [PMID: 22445344 DOI: 10.1016/j.neuron.2012.02.015] [Citation(s) in RCA: 438] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2012] [Indexed: 12/19/2022]
Abstract
Salient but aversive stimuli inhibit the majority of dopamine (DA) neurons in the ventral tegmental area (VTA) and cause conditioned place aversion (CPA). The cellular mechanism underlying DA neuron inhibition has not been investigated and the causal link to behavior remains elusive. Here, we show that GABA neurons of the VTA inhibit DA neurons through neurotransmission at GABA(A) receptors. We also observe that GABA neurons increase their firing in response to a footshock and provide evidence that driving GABA neurons with optogenetic effectors is sufficient to affect behavior. Taken together, our data demonstrate that synaptic inhibition of DA neurons drives place aversion.
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Affiliation(s)
- Kelly R Tan
- Department of Basic Neurosciences, University of Geneva, 1211 Geneva, Switzerland
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