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Richman EB, Ticea N, Allen WE, Deisseroth K, Luo L. Neural landscape diffusion resolves conflicts between needs across time. Nature 2023; 623:571-579. [PMID: 37938783 PMCID: PMC10651489 DOI: 10.1038/s41586-023-06715-z] [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] [Received: 09/23/2022] [Accepted: 10/04/2023] [Indexed: 11/09/2023]
Abstract
Animals perform flexible goal-directed behaviours to satisfy their basic physiological needs1-12. However, little is known about how unitary behaviours are chosen under conflicting needs. Here we reveal principles by which the brain resolves such conflicts between needs across time. We developed an experimental paradigm in which a hungry and thirsty mouse is given free choices between equidistant food and water. We found that mice collect need-appropriate rewards by structuring their choices into persistent bouts with stochastic transitions. High-density electrophysiological recordings during this behaviour revealed distributed single neuron and neuronal population correlates of a persistent internal goal state guiding future choices of the mouse. We captured these phenomena with a mathematical model describing a global need state that noisily diffuses across a shifting energy landscape. Model simulations successfully predicted behavioural and neural data, including population neural dynamics before choice transitions and in response to optogenetic thirst stimulation. These results provide a general framework for resolving conflicts between needs across time, rooted in the emergent properties of need-dependent state persistence and noise-driven shifts between behavioural goals.
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Affiliation(s)
- Ethan B Richman
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA
| | - Nicole Ticea
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | - William E Allen
- Neurosciences Graduate Program, Stanford University, Stanford, CA, USA
- Society of Fellows, Harvard University, Cambridge, MA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Department of Psychiatry and Behavioral Sciences, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
| | - Liqun Luo
- Department of Biology, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
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Lui JH, Nguyen ND, Grutzner SM, Darmanis S, Peixoto D, Wagner MJ, Allen WE, Kebschull JM, Richman EB, Ren J, Newsome WT, Quake SR, Luo L. Differential encoding in prefrontal cortex projection neuron classes across cognitive tasks. Cell 2021; 184:489-506.e26. [PMID: 33338423 PMCID: PMC7935083 DOI: 10.1016/j.cell.2020.11.046] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [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: 02/28/2020] [Revised: 08/04/2020] [Accepted: 11/25/2020] [Indexed: 12/13/2022]
Abstract
Single-cell transcriptomics has been widely applied to classify neurons in the mammalian brain, while systems neuroscience has historically analyzed the encoding properties of cortical neurons without considering cell types. Here we examine how specific transcriptomic types of mouse prefrontal cortex (PFC) projection neurons relate to axonal projections and encoding properties across multiple cognitive tasks. We found that most types projected to multiple targets, and most targets received projections from multiple types, except PFC→PAG (periaqueductal gray). By comparing Ca2+ activity of the molecularly homogeneous PFC→PAG type against two heterogeneous classes in several two-alternative choice tasks in freely moving mice, we found that all task-related signals assayed were qualitatively present in all examined classes. However, PAG-projecting neurons most potently encoded choice in cued tasks, whereas contralateral PFC-projecting neurons most potently encoded reward context in an uncued task. Thus, task signals are organized redundantly, but with clear quantitative biases across cells of specific molecular-anatomical characteristics.
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Affiliation(s)
- Jan H Lui
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
| | - Nghia D Nguyen
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Program in Neuroscience, Harvard University, Boston, MA 02115, USA
| | - Sophie M Grutzner
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Spyros Darmanis
- Departments of Bioengineering and Applied Physics, Chan Zuckerberg Biohub, Stanford University, Stanford, CA 94305, USA
| | - Diogo Peixoto
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA
| | - Mark J Wagner
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - William E Allen
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Neurosciences PhD Program, Stanford University, Stanford, CA 94305, USA
| | - Justus M Kebschull
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Ethan B Richman
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Neurosciences PhD Program, Stanford University, Stanford, CA 94305, USA
| | - Jing Ren
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - William T Newsome
- Department of Neurobiology, Stanford University, Stanford, CA 94305, USA
| | - Stephen R Quake
- Departments of Bioengineering and Applied Physics, Chan Zuckerberg Biohub, Stanford University, Stanford, CA 94305, USA.
| | - Liqun Luo
- Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
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Kebschull JM, Richman EB, Ringach N, Friedmann D, Albarran E, Kolluru SS, Jones RC, Allen WE, Wang Y, Cho SW, Zhou H, Ding JB, Chang HY, Deisseroth K, Quake SR, Luo L. Cerebellar nuclei evolved by repeatedly duplicating a conserved cell-type set. Science 2020; 370:eabd5059. [PMID: 33335034 PMCID: PMC8510508 DOI: 10.1126/science.abd5059] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [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: 06/24/2020] [Accepted: 10/26/2020] [Indexed: 11/02/2022]
Abstract
How have complex brains evolved from simple circuits? Here we investigated brain region evolution at cell-type resolution in the cerebellar nuclei, the output structures of the cerebellum. Using single-nucleus RNA sequencing in mice, chickens, and humans, as well as STARmap spatial transcriptomic analysis and whole-central nervous system projection tracing, we identified a conserved cell-type set containing two region-specific excitatory neuron classes and three region-invariant inhibitory neuron classes. This set constitutes an archetypal cerebellar nucleus that was repeatedly duplicated to form new regions. The excitatory cell class that preferentially funnels information to lateral frontal cortices in mice becomes predominant in the massively expanded human lateral nucleus. Our data suggest a model of brain region evolution by duplication and divergence of entire cell-type sets.
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Affiliation(s)
| | - Ethan B Richman
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Neurosciences Program, Stanford University, Stanford, CA 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Noam Ringach
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Drew Friedmann
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Eddy Albarran
- Neurosciences Program, Stanford University, Stanford, CA 94305, USA
| | - Sai Saroja Kolluru
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, Stanford, CA 94305, USA
| | - Robert C Jones
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - William E Allen
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Neurosciences Program, Stanford University, Stanford, CA 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Society of Fellows, Harvard University, Cambridge, MA 02138, USA
| | - Ying Wang
- Department of Animal Science, University of California, Davis, CA 95616, USA
| | - Seung Woo Cho
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA 94305, USA
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, CA 95616, USA
| | - Jun B Ding
- Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Stephen R Quake
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, Stanford, CA 94305, USA
| | - Liqun Luo
- Department of Biology, Stanford University, Stanford, CA 94305, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
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Richman EB, Luo L. Suppressing Memories by Shrinking the Vesicle Pool. Neuron 2019; 101:5-7. [PMID: 30605657 DOI: 10.1016/j.neuron.2018.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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] [Indexed: 11/18/2022]
Abstract
The cohesin complex regulates cellular functions spanning cell division and neuronal morphogenesis. Now, Phan et al. uncover a role for the cohesin complex in regulating memory acquisition and the size of the synaptic and dense-core vesicle pool.
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Affiliation(s)
- Ethan B Richman
- Neurosciences Graduate Program, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
| | - Liqun Luo
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
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Allen WE, Kauvar IV, Chen MZ, Richman EB, Yang SJ, Chan K, Gradinaru V, Deverman BE, Luo L, Deisseroth K. Global Representations of Goal-Directed Behavior in Distinct Cell Types of Mouse Neocortex. Neuron 2017; 94:891-907.e6. [PMID: 28521139 PMCID: PMC5723385 DOI: 10.1016/j.neuron.2017.04.017] [Citation(s) in RCA: 216] [Impact Index Per Article: 30.9] [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: 06/17/2016] [Revised: 01/26/2017] [Accepted: 04/11/2017] [Indexed: 11/27/2022]
Abstract
The successful planning and execution of adaptive behaviors in mammals may require long-range coordination of neural networks throughout cerebral cortex. The neuronal implementation of signals that could orchestrate cortex-wide activity remains unclear. Here, we develop and apply methods for cortex-wide Ca2+ imaging in mice performing decision-making behavior and identify a global cortical representation of task engagement encoded in the activity dynamics of both single cells and superficial neuropil distributed across the majority of dorsal cortex. The activity of multiple molecularly defined cell types was found to reflect this representation with type-specific dynamics. Focal optogenetic inhibition tiled across cortex revealed a crucial role for frontal cortex in triggering this cortex-wide phenomenon; local inhibition of this region blocked both the cortex-wide response to task-initiating cues and the voluntary behavior. These findings reveal cell-type-specific processes in cortex for globally representing goal-directed behavior and identify a major cortical node that gates the global broadcast of task-related information.
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Affiliation(s)
- William E Allen
- Neurosciences Graduate Program, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Isaac V Kauvar
- Electrical Engineering Graduate Program, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Michael Z Chen
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Ethan B Richman
- Neurosciences Graduate Program, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Samuel J Yang
- Electrical Engineering Graduate Program, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Ken Chan
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Viviana Gradinaru
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Benjamin E Deverman
- Division of Biology and Bioengineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Liqun Luo
- Department of Biology, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA.
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA.
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