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Wang H, Flores RJ, Yarur HE, Limoges A, Bravo-Rivera H, Casello SM, Loomba N, Enriquez-Traba J, Arenivar M, Wang Q, Ganley R, Ramakrishnan C, Fenno LE, Kim Y, Deisseroth K, Or G, Dong C, Hoon MA, Tian L, Tejeda HA. Prefrontal cortical dynorphin peptidergic transmission constrains threat-driven behavioral and network states. Neuron 2024:S0896-6273(24)00193-4. [PMID: 38614102 DOI: 10.1016/j.neuron.2024.03.015] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 01/19/2024] [Accepted: 03/13/2024] [Indexed: 04/15/2024]
Abstract
Prefrontal cortical (PFC) circuits provide top-down control of threat reactivity. This includes ventromedial PFC (vmPFC) circuitry, which plays a role in suppressing fear-related behavioral states. Dynorphin (Dyn) has been implicated in mediating negative affect and maladaptive behaviors induced by severe threats and is expressed in limbic circuits, including the vmPFC. However, there is a critical knowledge gap in our understanding of how vmPFC Dyn-expressing neurons and Dyn transmission detect threats and regulate expression of defensive behaviors. Here, we demonstrate that Dyn cells are broadly activated by threats and release Dyn locally in the vmPFC to limit passive defensive behaviors. We further demonstrate that vmPFC Dyn-mediated signaling promotes a switch of vmPFC networks to a fear-related state. In conclusion, we reveal a previously unknown role of vmPFC Dyn neurons and Dyn neuropeptidergic transmission in suppressing defensive behaviors in response to threats via state-driven changes in vmPFC networks.
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Affiliation(s)
- Huikun Wang
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Rodolfo J Flores
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Hector E Yarur
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Aaron Limoges
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA; Columbia University - NIH Graduate Partnership Program, National Institutes of Health, Bethesda, MD, USA
| | - Hector Bravo-Rivera
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Sanne M Casello
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Niharika Loomba
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Juan Enriquez-Traba
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Miguel Arenivar
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA; Brown University - NIH Graduate Partnership Program, National Institutes of Health, Bethesda, MD, USA
| | - Queenie Wang
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Robert Ganley
- Molecular Genetics Section, Laboratory of Sensory Biology, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
| | - Charu Ramakrishnan
- Departments of Bioengineering and Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Lief E Fenno
- Departments of Bioengineering and Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Yoon Kim
- Departments of Bioengineering and Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Karl Deisseroth
- Departments of Bioengineering and Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Grace Or
- Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, CA, USA
| | - Chunyang Dong
- Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, CA, USA
| | - Mark A Hoon
- Molecular Genetics Section, Laboratory of Sensory Biology, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA
| | - Lin Tian
- Department of Biochemistry and Molecular Medicine, University of California, Davis, Davis, CA, USA; Max Planck Florida Institute for Neuroscience, Jupiter, FL, USA
| | - Hugo A Tejeda
- Neuromodulation and Synaptic Integration Unit, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA.
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Wagner MJ, Savall J, Hernandez O, Mel G, Inan H, Rumyantsev O, Lecoq J, Kim TH, Li JZ, Ramakrishnan C, Deisseroth K, Luo L, Ganguli S, Schnitzer MJ. A neural circuit state change underlying skilled movements. Cell 2021; 184:3731-3747.e21. [PMID: 34214470 PMCID: PMC8844704 DOI: 10.1016/j.cell.2021.06.001] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [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: 10/07/2020] [Revised: 05/09/2021] [Accepted: 06/01/2021] [Indexed: 11/21/2022]
Abstract
In motor neuroscience, state changes are hypothesized to time-lock neural assemblies coordinating complex movements, but evidence for this remains slender. We tested whether a discrete change from more autonomous to coherent spiking underlies skilled movement by imaging cerebellar Purkinje neuron complex spikes in mice making targeted forelimb-reaches. As mice learned the task, millimeter-scale spatiotemporally coherent spiking emerged ipsilateral to the reaching forelimb, and consistent neural synchronization became predictive of kinematic stereotypy. Before reach onset, spiking switched from more disordered to internally time-locked concerted spiking and silence. Optogenetic manipulations of cerebellar feedback to the inferior olive bi-directionally modulated neural synchronization and reaching direction. A simple model explained the reorganization of spiking during reaching as reflecting a discrete bifurcation in olivary network dynamics. These findings argue that to prepare learned movements, olivo-cerebellar circuits enter a self-regulated, synchronized state promoting motor coordination. State changes facilitating behavioral transitions may generalize across neural systems.
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Affiliation(s)
- Mark J Wagner
- Neurosciences Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA.
| | - Joan Savall
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA
| | | | - Gabriel Mel
- Neurosciences Program, Stanford University, Stanford, CA 94305, USA
| | - Hakan Inan
- CNC Program, Stanford University, Stanford, CA 94305, USA; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Oleg Rumyantsev
- CNC Program, Stanford University, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Jérôme Lecoq
- CNC Program, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Tony Hyun Kim
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Jin Zhong Li
- CNC Program, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Charu Ramakrishnan
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Karl Deisseroth
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Liqun Luo
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Surya Ganguli
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Mark J Schnitzer
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Department of Biology, Stanford University, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA.
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Abstract
The mammalian brain is a densely interconnected network that consists of millions to billions of neurons. Decoding how information is represented and processed by this neural circuitry requires the ability to capture and manipulate the dynamics of large populations at high speed and high resolution over a large area of the brain. Although the use of optical approaches by the neuroscience community has rapidly increased over the past two decades, most microscopy approaches are unable to record the activity of all neurons comprising a functional network across the mammalian brain at relevant temporal and spatial resolutions. In this review, we survey the recent development in optical technologies for Ca2+ imaging in this regard and provide an overview of the strengths and limitations of each modality and its potential for scalability. We provide guidance from the perspective of a biological user driven by the typical biological applications and sample conditions. We also discuss the potential for future advances and synergies that could be obtained through hybrid approaches or other modalities.
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Affiliation(s)
- Siegfried Weisenburger
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, New York 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, New York 10065, USA
- Kavli Neural Systems Institute, The Rockefeller University, New York, New York 10065, USA
- Research Institute of Molecular Pathology, 1030 Vienna, Austria;
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