1
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Phalip A, Netser S, Wagner S. Understanding the neurobiology of social behavior through exploring brain-wide dynamics of neural activity. Neurosci Biobehav Rev 2024; 165:105856. [PMID: 39159735 DOI: 10.1016/j.neubiorev.2024.105856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 08/11/2024] [Accepted: 08/14/2024] [Indexed: 08/21/2024]
Abstract
Social behavior is highly complex and adaptable. It can be divided into multiple temporal stages: detection, approach, and consummatory behavior. Each stage can be further divided into several cognitive and behavioral processes, such as perceiving social cues, evaluating the social and non-social contexts, and recognizing the internal/emotional state of others. Recent studies have identified numerous brain-wide circuits implicated in social behavior and suggested the existence of partially overlapping functional brain networks underlying various types of social and non-social behavior. However, understanding the brain-wide dynamics underlying social behavior remains challenging, and several brain-scale dynamics (macro-, meso-, and micro-scale levels) need to be integrated. Here, we suggest leveraging new tools and concepts to explore social brain networks and integrate those different levels. These include studying the expression of immediate-early genes throughout the entire brain to impartially define the structure of the neuronal networks involved in a given social behavior. Then, network dynamics could be investigated using electrode arrays or multi-channel fiber photometry. Finally, tools like high-density silicon probes and miniscopes can probe neural activity in specific areas and across neuronal populations at the single-cell level.
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Affiliation(s)
- Adèle Phalip
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel.
| | - Shai Netser
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel
| | - Shlomo Wagner
- Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel
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2
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Giez C, Noack C, Sakib E, Hofacker LM, Repnik U, Bramkamp M, Bosch TCG. Satiety controls behavior in Hydra through an interplay of pre-enteric and central nervous system-like neuron populations. Cell Rep 2024; 43:114210. [PMID: 38787723 DOI: 10.1016/j.celrep.2024.114210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 03/11/2024] [Accepted: 04/23/2024] [Indexed: 05/26/2024] Open
Abstract
Hunger and satiety can have an influence on decision-making, sensory processing, and motor behavior by altering the internal state of the brain. This process necessitates the integration of peripheral sensory stimuli into the central nervous system. Here, we show how animals without a central nervous system such as the cnidarian Hydra measure and integrate satiety into neuronal circuits and which specific neuronal populations are involved. We demonstrate that this simple nervous system, previously referred to as diffuse, has an endodermal subpopulation (N4) similar to the enteric nervous system (feeding-associated behavior) and an ectodermal population (N3) that performs central nervous system-like functions (physiology/motor). This view of a supposedly simple nervous system could open an important window into the origin of more complex nervous systems.
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Affiliation(s)
- Christoph Giez
- Zoological Institute, University of Kiel, Am Botanischen Garten 1-9, 24118 Kiel, Germany; Neural Circuits and Evolution Laboratory, Francis Crick Institute, London NW1 1AT, UK.
| | - Christopher Noack
- Zoological Institute, University of Kiel, Am Botanischen Garten 1-9, 24118 Kiel, Germany
| | - Ehsan Sakib
- Zoological Institute, University of Kiel, Am Botanischen Garten 1-9, 24118 Kiel, Germany
| | - Lisa-Marie Hofacker
- Zoological Institute, University of Kiel, Am Botanischen Garten 1-9, 24118 Kiel, Germany
| | - Urska Repnik
- Centrale Microscopy, University of Kiel, Am Botanischen Garten 1-9, 24118 Kiel, Germany
| | - Marc Bramkamp
- Centrale Microscopy, University of Kiel, Am Botanischen Garten 1-9, 24118 Kiel, Germany; Institute for General Microbiology, University of Kiel, Am Botanischen Garten 1-9, 24118 Kiel, Germany
| | - Thomas C G Bosch
- Zoological Institute, University of Kiel, Am Botanischen Garten 1-9, 24118 Kiel, Germany.
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3
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Haley JA, Chalasani SH. C. elegans foraging as a model for understanding the neuronal basis of decision-making. Cell Mol Life Sci 2024; 81:252. [PMID: 38849591 PMCID: PMC11335288 DOI: 10.1007/s00018-024-05223-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/27/2024] [Accepted: 03/30/2024] [Indexed: 06/09/2024]
Abstract
Animals have evolved to seek, select, and exploit food sources in their environment. Collectively termed foraging, these ubiquitous behaviors are necessary for animal survival. As a foundation for understanding foraging, behavioral ecologists established early theoretical and mathematical frameworks which have been subsequently refined and supported by field and laboratory studies of foraging animals. These simple models sought to explain how animals decide which strategies to employ when locating food, what food items to consume, and when to explore the environment for new food sources. These foraging decisions involve integration of prior experience with multimodal sensory information about the animal's current environment and internal state. We suggest that the nematode Caenorhabditis elegans is well-suited for a high-resolution analysis of complex goal-oriented behaviors such as foraging. We focus our discussion on behavioral studies highlighting C. elegans foraging on bacteria and summarize what is known about the underlying neuronal and molecular pathways. Broadly, we suggest that this simple model system can provide a mechanistic understanding of decision-making and present additional avenues for advancing our understanding of complex behavioral processes.
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Affiliation(s)
- Jessica A Haley
- Neurosciences Graduate Program, University of California San Diego, La Jolla, CA, 92093, USA
- Molecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | - Sreekanth H Chalasani
- Molecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, 92037, USA.
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4
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Chen AB, Duque M, Wang VM, Dhanasekar M, Mi X, Rymbek A, Tocquer L, Narayan S, Prober D, Yu G, Wyart C, Engert F, Ahrens MB. Norepinephrine changes behavioral state via astroglial purinergic signaling. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595576. [PMID: 38826423 PMCID: PMC11142163 DOI: 10.1101/2024.05.23.595576] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Both neurons and glia communicate via diffusible neuromodulatory substances, but the substrates of computation in such neuromodulatory networks are unclear. During behavioral transitions in the larval zebrafish, the neuromodulator norepinephrine drives fast excitation and delayed inhibition of behavior and circuit activity. We find that the inhibitory arm of this feedforward motif is implemented by astroglial purinergic signaling. Neuromodulator imaging, behavioral pharmacology, and perturbations of neurons and astroglia reveal that norepinephrine triggers astroglial release of adenosine triphosphate, extracellular conversion into adenosine, and behavioral suppression through activation of hindbrain neuronal adenosine receptors. This work, along with a companion piece by Lefton and colleagues demonstrating an analogous pathway mediating the effect of norepinephrine on synaptic connectivity in mice, identifies a computational and behavioral role for an evolutionarily conserved astroglial purinergic signaling axis in norepinephrine-mediated behavioral and brain state transitions.
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Affiliation(s)
- Alex B. Chen
- Janelia Research Campus, Howard Hughes Medical Institute; Ashburn, VA 20147, USA
- Department of Molecular and Cellular Biology, Harvard University; Cambridge, MA 02138, USA
- Graduate Program in Neuroscience, Harvard Medical School; Boston, MA 02115, USA
| | - Marc Duque
- Department of Molecular and Cellular Biology, Harvard University; Cambridge, MA 02138, USA
- Graduate Program in Neuroscience, Harvard Medical School; Boston, MA 02115, USA
| | - Vickie M. Wang
- Department of Molecular and Cellular Biology, Harvard University; Cambridge, MA 02138, USA
- Graduate Program in Neuroscience, Harvard Medical School; Boston, MA 02115, USA
| | - Mahalakshmi Dhanasekar
- Sorbonne Université, Paris Brain Institute (Institut du Cerveau, ICM), Institut National de la Santé et de la Recherche Médicale U1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche 7225, Assistance Publique–Hôpitaux de Paris, Campus Hospitalier Pitié-Salpêtrière, Paris, France
| | - Xuelong Mi
- Bradley Department of Electrical and Computer Engineering; Virginia Polytechnic Institute and State University; Arlington, VA 22203, USA
| | - Altyn Rymbek
- Tianqiao and Chrissy Chen Institute for Neuroscience, Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Loeva Tocquer
- Sorbonne Université, Paris Brain Institute (Institut du Cerveau, ICM), Institut National de la Santé et de la Recherche Médicale U1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche 7225, Assistance Publique–Hôpitaux de Paris, Campus Hospitalier Pitié-Salpêtrière, Paris, France
| | - Sujatha Narayan
- Janelia Research Campus, Howard Hughes Medical Institute; Ashburn, VA 20147, USA
- Present address: Allen Institute for Neural Dynamics; Seattle, WA 98109, USA
| | - David Prober
- Tianqiao and Chrissy Chen Institute for Neuroscience, Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Guoqiang Yu
- Department of Automation, Tsinghua University; Beijing 100084, P.R. China
| | - Claire Wyart
- Sorbonne Université, Paris Brain Institute (Institut du Cerveau, ICM), Institut National de la Santé et de la Recherche Médicale U1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche 7225, Assistance Publique–Hôpitaux de Paris, Campus Hospitalier Pitié-Salpêtrière, Paris, France
| | - Florian Engert
- Department of Molecular and Cellular Biology, Harvard University; Cambridge, MA 02138, USA
| | - Misha B. Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute; Ashburn, VA 20147, USA
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5
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Sridhar G, Vergassola M, Marques JC, Orger MB, Costa AC, Wyart C. Uncovering multiscale structure in the variability of larval zebrafish navigation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.16.594521. [PMID: 38798455 PMCID: PMC11118365 DOI: 10.1101/2024.05.16.594521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Animals chain movements into long-lived motor strategies, resulting in variability that ultimately reflects the interplay between internal states and environmental cues. To reveal structure in such variability, we build models that bridges across time scales that enable a quantitative comparison of behavioral phenotypes among individuals. Applied to larval zebrafish exposed to diverse sensory cues, we uncover a hierarchy of long-lived motor strategies, dominated by changes in orientation distinguishing cruising and wandering strategies. Environmental cues induce preferences along these modes at the population level: while fish cruise in the light, they wander in response to aversive (dark) stimuli or in search for prey. Our method enables us to encode the behavioral dynamics of each individual fish in the transitions among coarse-grained motor strategies. By doing so, we uncover a hierarchical structure to the phenotypic variability that corresponds to exploration-exploitation trade-offs. Within a wide range of sensory cues, a major source of variation among fish is driven by prior and immediate exposure to prey that induces exploitation phenotypes. However, a large degree of variability is unexplained by environmental cues, pointing to hidden states that override the sensory context to induce contrasting exploration-exploitation phenotypes. Altogether, our approach extracts the timescales of motor strategies deployed during navigation, exposing undiscovered structure among individuals and pointing to internal states tuned by prior experience.
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6
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Fine JM, Yoo SBM, Hayden BY. Control over a mixture of policies determines change of mind topology during continuous choice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590154. [PMID: 38712284 PMCID: PMC11071291 DOI: 10.1101/2024.04.18.590154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Behavior is naturally organized into categorically distinct states with corresponding patterns of neural activity; how does the brain control those states? We propose that states are regulated by specific neural processes that implement meta-control that can blend simpler control processes. To test this hypothesis, we recorded from neurons in the dorsal anterior cingulate cortex (dACC) and dorsal premotor cortex (PMd) while macaques performed a continuous pursuit task with two moving prey that followed evasive strategies. We used a novel control theoretic approach to infer subjects' moment-to-moment latent control variables, which in turn dictated their blend of distinct identifiable control processes. We identified low-dimensional subspaces in neuronal responses that reflected the current strategy, the value of the pursued target, and the relative value of the two targets. The top two principal components of activity tracked changes of mind in abstract and change-type-specific formats, respectively. These results indicate that control of behavioral state reflects the interaction of brain processes found in dorsal prefrontal regions that implement a mixture over low-level control policies.
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7
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Braun D, Rosenberg AM, Rabaniam E, Haruvi R, Malamud D, Barbara R, Aiznkot T, Levavi-Sivan B, Kawashima T. High-resolution tracking of unconfined zebrafish behavior reveals stimulatory and anxiolytic effects of psilocybin. Mol Psychiatry 2024; 29:1046-1062. [PMID: 38233467 PMCID: PMC11176078 DOI: 10.1038/s41380-023-02391-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 12/12/2023] [Accepted: 12/19/2023] [Indexed: 01/19/2024]
Abstract
Serotonergic psychedelics are emerging therapeutics for psychiatric disorders, yet their underlying mechanisms of action in the brain remain largely elusive. Here, we developed a wide-field behavioral tracking system for larval zebrafish and investigated the effects of psilocybin, a psychedelic serotonin receptor agonist. Machine learning analyses of precise body kinematics identified latent behavioral states reflecting spontaneous exploration, visually-driven rapid swimming, and irregular swim patterns following stress exposure. Using this method, we found that acute psilocybin treatment has two behavioral effects: [i] facilitation of spontaneous exploration ("stimulatory") and [ii] prevention of irregular swim patterns following stress exposure ("anxiolytic"). These effects differed from the effect of acute SSRI treatment and were rather similar to the effect of ketamine treatment. Neural activity imaging in the dorsal raphe nucleus suggested that psilocybin inhibits serotonergic neurons by activating local GABAergic neurons, consistent with psychedelic-induced suppression of serotonergic neurons in mammals. These findings pave the way for using larval zebrafish to elucidate neural mechanisms underlying the behavioral effects of serotonergic psychedelics.
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Affiliation(s)
- Dotan Braun
- Department of Brain Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot, Israel
- The Jerusalem Mental Health Center, Jerusalem, Israel
| | - Ayelet M Rosenberg
- Department of Brain Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot, Israel
| | - Elad Rabaniam
- Department of Brain Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot, Israel
| | - Ravid Haruvi
- Department of Brain Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot, Israel
| | - Dorel Malamud
- Department of Brain Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot, Israel
| | - Rani Barbara
- Department of Brain Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot, Israel
| | - Tomer Aiznkot
- Department of Animal Sciences, The Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, 229 Herzl Street, Rehovot, Israel
| | - Berta Levavi-Sivan
- Department of Animal Sciences, The Robert H. Smith Faculty of Agriculture, Food, and Environment, Hebrew University of Jerusalem, 229 Herzl Street, Rehovot, Israel
| | - Takashi Kawashima
- Department of Brain Sciences, Weizmann Institute of Science, 234 Herzl Street, Rehovot, Israel.
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8
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Yuste R, Cossart R, Yaksi E. Neuronal ensembles: Building blocks of neural circuits. Neuron 2024; 112:875-892. [PMID: 38262413 PMCID: PMC10957317 DOI: 10.1016/j.neuron.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 06/07/2023] [Accepted: 12/13/2023] [Indexed: 01/25/2024]
Abstract
Neuronal ensembles, defined as groups of neurons displaying recurring patterns of coordinated activity, represent an intermediate functional level between individual neurons and brain areas. Novel methods to measure and optically manipulate the activity of neuronal populations have provided evidence of ensembles in the neocortex and hippocampus. Ensembles can be activated intrinsically or in response to sensory stimuli and play a causal role in perception and behavior. Here we review ensemble phenomenology, developmental origin, biophysical and synaptic mechanisms, and potential functional roles across different brain areas and species, including humans. As modular units of neural circuits, ensembles could provide a mechanistic underpinning of fundamental brain processes, including neural coding, motor planning, decision-making, learning, and adaptability.
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Affiliation(s)
- Rafael Yuste
- NeuroTechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA.
| | - Rosa Cossart
- Inserm, INMED, Turing Center for Living Systems Aix-Marseille University, Marseille, France.
| | - Emre Yaksi
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway; Koç University Research Center for Translational Medicine, Koç University School of Medicine, Istanbul, Turkey.
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9
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Manley J, Vaziri A. Whole-brain neural substrates of behavioral variability in the larval zebrafish. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.03.583208. [PMID: 38496592 PMCID: PMC10942351 DOI: 10.1101/2024.03.03.583208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Animals engaged in naturalistic behavior can exhibit a large degree of behavioral variability even under sensory invariant conditions. Such behavioral variability can include not only variations of the same behavior, but also variability across qualitatively different behaviors driven by divergent cognitive states, such as fight-or-flight decisions. However, the neural circuit mechanisms that generate such divergent behaviors across trials are not well understood. To investigate this question, here we studied the visual-evoked responses of larval zebrafish to moving objects of various sizes, which we found exhibited highly variable and divergent responses across repetitions of the same stimulus. Given that the neuronal circuits underlying such behaviors span sensory, motor, and other brain areas, we built a novel Fourier light field microscope which enables high-resolution, whole-brain imaging of larval zebrafish during behavior. This enabled us to screen for neural loci which exhibited activity patterns correlated with behavioral variability. We found that despite the highly variable activity of single neurons, visual stimuli were robustly encoded at the population level, and the visual-encoding dimensions of neural activity did not explain behavioral variability. This robustness despite apparent single neuron variability was due to the multi-dimensional geometry of the neuronal population dynamics: almost all neural dimensions that were variable across individual trials, i.e. the "noise" modes, were orthogonal to those encoding for sensory information. Investigating this neuronal variability further, we identified two sparsely-distributed, brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations predicted single-trial behavior seconds before stimulus onset, indicating they encoded time-varying internal modulating behavior, perhaps organizing behavior over longer timescales or enabling flexible behavior routines dependent on the animal's internal state. Our results provide the first whole-brain confirmation that sensory, motor, and internal variables are encoded in a highly mixed fashion throughout the brain and demonstrate that de-mixing each of these components at the neuronal population level is critical to understanding the mechanisms underlying the brain's remarkable flexibility and robustness.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
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10
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Palieri V, Paoli E, Wu YK, Haesemeyer M, Grunwald Kadow IC, Portugues R. The preoptic area and dorsal habenula jointly support homeostatic navigation in larval zebrafish. Curr Biol 2024; 34:489-504.e7. [PMID: 38211586 PMCID: PMC10849091 DOI: 10.1016/j.cub.2023.12.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/22/2023] [Accepted: 12/11/2023] [Indexed: 01/13/2024]
Abstract
Animals must maintain physiological processes within an optimal temperature range despite changes in their environment. Through behavioral assays, whole-brain functional imaging, and neural ablations, we show that larval zebrafish, an ectothermic vertebrate, achieves thermoregulation through homeostatic navigation-non-directional and directional movements toward the temperature closest to its physiological setpoint. A brain-wide circuit encompassing several brain regions enables this behavior. We identified the preoptic area of the hypothalamus (PoA) as a key brain structure in triggering non-directional reorientation when thermal conditions are worsening. This result shows an evolutionary conserved role of the PoA as principal thermoregulator of the brain also in ectotherms. We further show that the habenula (Hb)-interpeduncular nucleus (IPN) circuit retains a short-term memory of the sensory history to support the generation of coherent directed movements even in the absence of continuous sensory cues. We finally provide evidence that this circuit may not be exclusive for temperature but may convey a more abstract representation of relative valence of physiologically meaningful stimuli regardless of their specific identity to enable homeostatic navigation.
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Affiliation(s)
- Virginia Palieri
- Institute of Neuroscience, Technical University of Munich, Biedersteiner Strasse 29, 80802 Munich, Germany; School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Emanuele Paoli
- Institute of Neuroscience, Technical University of Munich, Biedersteiner Strasse 29, 80802 Munich, Germany
| | - You Kure Wu
- Institute of Neuroscience, Technical University of Munich, Biedersteiner Strasse 29, 80802 Munich, Germany
| | - Martin Haesemeyer
- Department of Neuroscience, The Ohio State University College of Medicine, Columbus, OH 43210, USA
| | - Ilona C Grunwald Kadow
- School of Life Sciences, Technical University of Munich, Freising, Germany; Institute of Physiology II, University of Bonn, Medical Faculty (UKB), Nussallee 11, 53115 Bonn, Germany.
| | - Ruben Portugues
- Institute of Neuroscience, Technical University of Munich, Biedersteiner Strasse 29, 80802 Munich, Germany; Munich Cluster of Systems Neurology (SyNergy), Feodor-Lynen-Str. 17, 81377 Munich, Germany.
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11
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Chai Y, Qi K, Wu Y, Li D, Tan G, Guo Y, Chu J, Mu Y, Shen C, Wen Q. All-optical interrogation of brain-wide activity in freely swimming larval zebrafish. iScience 2024; 27:108385. [PMID: 38205255 PMCID: PMC10776927 DOI: 10.1016/j.isci.2023.108385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/22/2023] [Accepted: 10/30/2023] [Indexed: 01/12/2024] Open
Abstract
We introduce an all-optical technique that enables volumetric imaging of brain-wide calcium activity and targeted optogenetic stimulation of specific brain regions in unrestrained larval zebrafish. The system consists of three main components: a 3D tracking module, a dual-color fluorescence imaging module, and a real-time activity manipulation module. Our approach uses a sensitive genetically encoded calcium indicator in combination with a long Stokes shift red fluorescence protein as a reference channel, allowing the extraction of Ca2+ activity from signals contaminated by motion artifacts. The method also incorporates rapid 3D image reconstruction and registration, facilitating real-time selective optogenetic stimulation of different regions of the brain. By demonstrating that selective light activation of the midbrain regions in larval zebrafish could reliably trigger biased turning behavior and changes of brain-wide neural activity, we present a valuable tool for investigating the causal relationship between distributed neural circuit dynamics and naturalistic behavior.
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Affiliation(s)
- Yuming Chai
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Kexin Qi
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Yubin Wu
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Daguang Li
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Guodong Tan
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Yuqi Guo
- Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology and Center for Biomedical Optics and Molecular Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jun Chu
- Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology and Center for Biomedical Optics and Molecular Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yu Mu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Chen Shen
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
| | - Quan Wen
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Hefei National Research Center for Physical Sciences at the Microscale, Center for Integrative Imaging, University of Science and Technology of China, Hefei, China
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12
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Manley J, Demas J, Kim H, Traub FM, Vaziri A. Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.15.575721. [PMID: 38293036 PMCID: PMC10827059 DOI: 10.1101/2024.01.15.575721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.
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Affiliation(s)
- Jason Manley
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Jeffrey Demas
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
| | - Hyewon Kim
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Francisca Martínez Traub
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
| | - Alipasha Vaziri
- Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY 10065, USA
- The Kavli Neural Systems Institute, The Rockefeller University, New York, NY 10065, USA
- Lead Contact
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13
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Lai TT, Tsai YH, Liou CW, Fan CH, Hou YT, Yao TH, Chuang HL, Wu WL. The gut microbiota modulate locomotion via vagus-dependent glucagon-like peptide-1 signaling. NPJ Biofilms Microbiomes 2024; 10:2. [PMID: 38228675 DOI: 10.1038/s41522-024-00477-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 01/04/2024] [Indexed: 01/18/2024] Open
Abstract
Locomotor activity is an innate behavior that can be triggered by gut-motivated conditions, such as appetite and metabolic condition. Various nutrient-sensing receptors distributed in the vagal terminal in the gut are crucial for signal transduction from the gut to the brain. The levels of gut hormones are closely associated with the colonization status of the gut microbiota, suggesting a complicated interaction among gut bacteria, gut hormones, and the brain. However, the detailed mechanism underlying gut microbiota-mediated endocrine signaling in the modulation of locomotion is still unclear. Herein, we show that broad-spectrum antibiotic cocktail (ABX)-treated mice displayed hypolocomotion and elevated levels of the gut hormone glucagon-like peptide-1 (GLP-1). Blockade of the GLP-1 receptor and subdiaphragmatic vagal transmission rescued the deficient locomotor phenotype in ABX-treated mice. Activation of the GLP-1 receptor and vagal projecting brain regions led to hypolocomotion. Finally, selective antibiotic treatment dramatically increased serum GLP-1 levels and decreased locomotion. Colonizing Lactobacillus reuteri and Bacteroides thetaiotaomicron in microbiota-deficient mice suppressed GLP-1 levels and restored the hypolocomotor phenotype. Our findings identify a mechanism by which specific gut microbes mediate host motor behavior via the enteroendocrine and vagal-dependent neural pathways.
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Affiliation(s)
- Tzu-Ting Lai
- Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
- Department of Physiology, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
| | - Yu-Hsuan Tsai
- Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
- Department of Physiology, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
| | - Chia-Wei Liou
- Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
- Department of Physiology, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
| | - Ching-Hsiang Fan
- Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
| | - Yu-Tian Hou
- Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
| | - Tzu-Hsuan Yao
- Department of Physiology, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan
| | - Hsiao-Li Chuang
- National Laboratory Animal Center, National Applied Research Laboratories, Taipei, 115202, Taiwan
| | - Wei-Li Wu
- Institute of Basic Medical Sciences, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan.
- Department of Physiology, College of Medicine, National Cheng Kung University, 1 University Rd., Tainan, 70101, Taiwan.
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14
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Park CF, Barzegar-Keshteli M, Korchagina K, Delrocq A, Susoy V, Jones CL, Samuel ADT, Rahi SJ. Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation. Nat Methods 2024; 21:142-149. [PMID: 38052988 DOI: 10.1038/s41592-023-02096-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 10/20/2023] [Indexed: 12/07/2023]
Abstract
Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional neural network with ground-truth (GT) annotations of images representing different brain postures. For 3D images, this is very labor intensive. We introduce 'targeted augmentation', a method to automatically synthesize artificial annotations from a few manual annotations. Our method ('Targettrack') learns the internal deformations of the brain to synthesize annotations for new postures by deforming GT annotations. This reduces the need for manual annotation and proofreading. A graphical user interface allows the application of the method end-to-end. We demonstrate Targettrack on recordings where neurons are labeled as key points or 3D volumes. Analyzing freely moving animals exposed to odor pulses, we uncover rich patterns in interneuron dynamics, including switching neuronal entrainment on and off.
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Affiliation(s)
- Core Francisco Park
- Department of Physics and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Mahsa Barzegar-Keshteli
- Laboratory of the Physics of Biological Systems, Institute of Physics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Kseniia Korchagina
- Laboratory of the Physics of Biological Systems, Institute of Physics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ariane Delrocq
- Laboratory of the Physics of Biological Systems, Institute of Physics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Vladislav Susoy
- Department of Physics and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Corinne L Jones
- Swiss Data Science Center, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Aravinthan D T Samuel
- Department of Physics and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Sahand Jamal Rahi
- Laboratory of the Physics of Biological Systems, Institute of Physics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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15
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Abstract
Foraging animals optimize feeding decisions by adjusting both common and rare behavioral patterns. Here, we characterize the relationship between an animal's arousal state and a rare decision to leave a patch of bacterial food. Using long-term tracking and behavioral state classification, we find that food leaving decisions in Caenorhabditis elegans are coupled to arousal states across multiple timescales. Leaving emerges probabilistically over minutes from the high arousal roaming state, but is suppressed during the low arousal dwelling state. Immediately before leaving, animals have a brief acceleration in speed that appears as a characteristic signature of this behavioral motif. Neuromodulatory mutants and optogenetic manipulations that increase roaming have a coupled increase in leaving rates, and similarly acute manipulations that inhibit feeding induce both roaming and leaving. By contrast, inactivating a set of chemosensory neurons that depend on the cGMP-gated transduction channel TAX-4 uncouples roaming and leaving dynamics. In addition, tax-4-expressing sensory neurons promote lawn-leaving behaviors that are elicited by feeding inhibition. Our results indicate that sensory neurons responsive to both internal and external cues play an integrative role in arousal and foraging decisions.
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Affiliation(s)
- Elias Scheer
- Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior, The Rockefeller UniversityNew YorkUnited States
| | - Cornelia I Bargmann
- Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior, The Rockefeller UniversityNew YorkUnited States
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16
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Desai N, Bala P, Richardson R, Raper J, Zimmermann J, Hayden B. OpenApePose, a database of annotated ape photographs for pose estimation. eLife 2023; 12:RP86873. [PMID: 38078902 PMCID: PMC10712952 DOI: 10.7554/elife.86873] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023] Open
Abstract
Because of their close relationship with humans, non-human apes (chimpanzees, bonobos, gorillas, orangutans, and gibbons, including siamangs) are of great scientific interest. The goal of understanding their complex behavior would be greatly advanced by the ability to perform video-based pose tracking. Tracking, however, requires high-quality annotated datasets of ape photographs. Here we present OpenApePose, a new public dataset of 71,868 photographs, annotated with 16 body landmarks of six ape species in naturalistic contexts. We show that a standard deep net (HRNet-W48) trained on ape photos can reliably track out-of-sample ape photos better than networks trained on monkeys (specifically, the OpenMonkeyPose dataset) and on humans (COCO) can. This trained network can track apes almost as well as the other networks can track their respective taxa, and models trained without one of the six ape species can track the held-out species better than the monkey and human models can. Ultimately, the results of our analyses highlight the importance of large, specialized databases for animal tracking systems and confirm the utility of our new ape database.
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Affiliation(s)
- Nisarg Desai
- Department of Neuroscience and Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
| | - Praneet Bala
- Department of Computer Science, University of MinnesotaMinneapolisUnited States
| | - Rebecca Richardson
- Emory National Primate Research Center, Emory UniversityAtlantaUnited States
| | - Jessica Raper
- Emory National Primate Research Center, Emory UniversityAtlantaUnited States
| | - Jan Zimmermann
- Department of Neuroscience and Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
| | - Benjamin Hayden
- Department of Neuroscience and Center for Magnetic Resonance Research, University of MinnesotaMinneapolisUnited States
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17
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Roland PE. How far neuroscience is from understanding brains. Front Syst Neurosci 2023; 17:1147896. [PMID: 37867627 PMCID: PMC10585277 DOI: 10.3389/fnsys.2023.1147896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 07/31/2023] [Indexed: 10/24/2023] Open
Abstract
The cellular biology of brains is relatively well-understood, but neuroscientists have not yet generated a theory explaining how brains work. Explanations of how neurons collectively operate to produce what brains can do are tentative and incomplete. Without prior assumptions about the brain mechanisms, I attempt here to identify major obstacles to progress in neuroscientific understanding of brains and central nervous systems. Most of the obstacles to our understanding are conceptual. Neuroscience lacks concepts and models rooted in experimental results explaining how neurons interact at all scales. The cerebral cortex is thought to control awake activities, which contrasts with recent experimental results. There is ambiguity distinguishing task-related brain activities from spontaneous activities and organized intrinsic activities. Brains are regarded as driven by external and internal stimuli in contrast to their considerable autonomy. Experimental results are explained by sensory inputs, behavior, and psychological concepts. Time and space are regarded as mutually independent variables for spiking, post-synaptic events, and other measured variables, in contrast to experimental results. Dynamical systems theory and models describing evolution of variables with time as the independent variable are insufficient to account for central nervous system activities. Spatial dynamics may be a practical solution. The general hypothesis that measurements of changes in fundamental brain variables, action potentials, transmitter releases, post-synaptic transmembrane currents, etc., propagating in central nervous systems reveal how they work, carries no additional assumptions. Combinations of current techniques could reveal many aspects of spatial dynamics of spiking, post-synaptic processing, and plasticity in insects and rodents to start with. But problems defining baseline and reference conditions hinder interpretations of the results. Furthermore, the facts that pooling and averaging of data destroy their underlying dynamics imply that single-trial designs and statistics are necessary.
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Affiliation(s)
- Per E. Roland
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
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18
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Cropper EC, Perkins M, Jing J. Persistent modulatory actions and task switching in the feeding network of Aplysia. Curr Opin Neurobiol 2023; 82:102775. [PMID: 37625344 PMCID: PMC10530010 DOI: 10.1016/j.conb.2023.102775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 07/26/2023] [Accepted: 08/01/2023] [Indexed: 08/27/2023]
Abstract
The activity of multifunctional networks is configured by neuromodulators that exert persistent effects. This raises a question, does this impact the ability of a network to switch from one type of activity to another? We review studies that have addressed this question in the Aplysia feeding circuit. Task switching in this system occurs "asymmetrically." When there is a switch from egestion to ingestion neuromodulation impedes switching (creates a "negative bias"). When there is a switch from ingestion to egestion the biasing is "positive." Ingestion promotes subsequent egestion. We contrast mechanisms responsible for the two types of biasing and show that the observed asymmetry is a consequence of the fact that there is more than one set of egestive circuit parameters.
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Affiliation(s)
- Elizabeth C Cropper
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA.
| | - Matthew Perkins
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Jian Jing
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA; State Key Laboratory of Pharmaceutical Biotechnology, Institute for Brain Sciences, Chemistry and Biomedicine Innovation Center, Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Advanced Institute for Life Sciences, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, China
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19
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Washbourne P. Can we model autism using zebrafish? Dev Growth Differ 2023; 65:453-458. [PMID: 37623916 DOI: 10.1111/dgd.12888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 07/25/2023] [Accepted: 08/21/2023] [Indexed: 08/26/2023]
Abstract
Autism spectrum disorder (ASD) is one of the most common, heritable neuropsychiatric disorders in the world, affecting almost 1% of the population. The core symptoms used to diagnose ASD are decreased social interaction and increased repetitive behaviors. Despite the large number of affected individuals, the precise mechanisms that cause this disorder remain unclear. The identification of genes and environmental factors associated with ASD allows the study of the underlying mechanisms in animal models. Although ASD presents as a human disorder, based on recent advances in understanding their brain anatomy, physiology, behavior, and evolutionary conservation of neuronal cell types, I propose that zebrafish may provide novel insights into the etiology.
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Affiliation(s)
- Philip Washbourne
- Institute of Neuroscience, 1254 University of Oregon, Eugene, Oregon, USA
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20
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Voloh B, Maisson DJN, Cervera RL, Conover I, Zambre M, Hayden B, Zimmermann J. Hierarchical action encoding in prefrontal cortex of freely moving macaques. Cell Rep 2023; 42:113091. [PMID: 37656619 PMCID: PMC10591875 DOI: 10.1016/j.celrep.2023.113091] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 06/23/2023] [Accepted: 08/18/2023] [Indexed: 09/03/2023] Open
Abstract
Our natural behavioral repertoires include coordinated actions of characteristic types. To better understand how neural activity relates to the expression of actions and action switches, we studied macaques performing a freely moving foraging task in an open environment. We developed a novel analysis pipeline that can identify meaningful units of behavior, corresponding to recognizable actions such as sitting, walking, jumping, and climbing. On the basis of transition probabilities between these actions, we found that behavior is organized in a modular and hierarchical fashion. We found that, after regressing out many potential confounders, actions are associated with specific patterns of firing in each of six prefrontal brain regions and that, overall, encoding of action category is progressively stronger in more dorsal and more caudal prefrontal regions. Together, these results establish a link between selection of units of primate behavior on one hand and neuronal activity in prefrontal regions on the other.
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Affiliation(s)
- Benjamin Voloh
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - David J-N Maisson
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | | | - Indirah Conover
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Mrunal Zambre
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA
| | - Benjamin Hayden
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA; Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA; Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455, USA.
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21
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Atanas AA, Kim J, Wang Z, Bueno E, Becker M, Kang D, Park J, Kramer TS, Wan FK, Baskoylu S, Dag U, Kalogeropoulou E, Gomes MA, Estrem C, Cohen N, Mansinghka VK, Flavell SW. Brain-wide representations of behavior spanning multiple timescales and states in C. elegans. Cell 2023; 186:4134-4151.e31. [PMID: 37607537 PMCID: PMC10836760 DOI: 10.1016/j.cell.2023.07.035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 07/05/2023] [Accepted: 07/28/2023] [Indexed: 08/24/2023]
Abstract
Changes in an animal's behavior and internal state are accompanied by widespread changes in activity across its brain. However, how neurons across the brain encode behavior and how this is impacted by state is poorly understood. We recorded brain-wide activity and the diverse motor programs of freely moving C. elegans and built probabilistic models that explain how each neuron encodes quantitative behavioral features. By determining the identities of the recorded neurons, we created an atlas of how the defined neuron classes in the C. elegans connectome encode behavior. Many neuron classes have conjunctive representations of multiple behaviors. Moreover, although many neurons encode current motor actions, others integrate recent actions. Changes in behavioral state are accompanied by widespread changes in how neurons encode behavior, and we identify these flexible nodes in the connectome. Our results provide a global map of how the cell types across an animal's brain encode its behavior.
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Affiliation(s)
- Adam A Atanas
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungsoo Kim
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ziyu Wang
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Bueno
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - McCoy Becker
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Di Kang
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungyeon Park
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Talya S Kramer
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; MIT Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Flossie K Wan
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Saba Baskoylu
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ugur Dag
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elpiniki Kalogeropoulou
- School of Computing, University of Leeds, Leeds, UK; School of Biology, University of Leeds, Leeds, UK
| | - Matthew A Gomes
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cassi Estrem
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Netta Cohen
- School of Computing, University of Leeds, Leeds, UK
| | - Vikash K Mansinghka
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven W Flavell
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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22
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Schaffer ES, Mishra N, Whiteway MR, Li W, Vancura MB, Freedman J, Patel KB, Voleti V, Paninski L, Hillman EMC, Abbott LF, Axel R. The spatial and temporal structure of neural activity across the fly brain. Nat Commun 2023; 14:5572. [PMID: 37696814 PMCID: PMC10495430 DOI: 10.1038/s41467-023-41261-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 08/29/2023] [Indexed: 09/13/2023] Open
Abstract
What are the spatial and temporal scales of brainwide neuronal activity? We used swept, confocally-aligned planar excitation (SCAPE) microscopy to image all cells in a large volume of the brain of adult Drosophila with high spatiotemporal resolution while flies engaged in a variety of spontaneous behaviors. This revealed neural representations of behavior on multiple spatial and temporal scales. The activity of most neurons correlated (or anticorrelated) with running and flailing over timescales that ranged from seconds to a minute. Grooming elicited a weaker global response. Significant residual activity not directly correlated with behavior was high dimensional and reflected the activity of small clusters of spatially organized neurons that may correspond to genetically defined cell types. These clusters participate in the global dynamics, indicating that neural activity reflects a combination of local and broadly distributed components. This suggests that microcircuits with highly specified functions are provided with knowledge of the larger context in which they operate.
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Affiliation(s)
- Evan S Schaffer
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA.
| | - Neeli Mishra
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Matthew R Whiteway
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Statistics and the Grossman Center for the Statistics of Mind, Columbia University, New York, NY, 10027, USA
| | - Wenze Li
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Michelle B Vancura
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Jason Freedman
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
| | - Kripa B Patel
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Venkatakaushik Voleti
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
| | - Liam Paninski
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Statistics and the Grossman Center for the Statistics of Mind, Columbia University, New York, NY, 10027, USA
| | - Elizabeth M C Hillman
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA
- Department of Radiology, Columbia University, New York, NY, 10027, USA
| | - L F Abbott
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Physiology and Cellular Biophysics, Columbia University, New York, NY, 10032, USA
| | - Richard Axel
- Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Neuroscience, Columbia University, New York, NY, 10027, USA
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA
- Howard Hughes Medical Institute, Columbia University, New York, NY, 10027, USA
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23
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Bukwich M, Campbell MG, Zoltowski D, Kingsbury L, Tomov MS, Stern J, Kim HR, Drugowitsch J, Linderman SW, Uchida N. Competitive integration of time and reward explains value-sensitive foraging decisions and frontal cortex ramping dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.05.556267. [PMID: 37732217 PMCID: PMC10508756 DOI: 10.1101/2023.09.05.556267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
The ability to make advantageous decisions is critical for animals to ensure their survival. Patch foraging is a natural decision-making process in which animals decide when to leave a patch of depleting resources to search for a new one. To study the algorithmic and neural basis of patch foraging behavior in a controlled laboratory setting, we developed a virtual foraging task for head-fixed mice. Mouse behavior could be explained by ramp-to-threshold models integrating time and rewards antagonistically. Accurate behavioral modeling required inclusion of a slowly varying "patience" variable, which modulated sensitivity to time. To investigate the neural basis of this decision-making process, we performed dense electrophysiological recordings with Neuropixels probes broadly throughout frontal cortex and underlying subcortical areas. We found that decision variables from the reward integrator model were represented in neural activity, most robustly in frontal cortical areas. Regression modeling followed by unsupervised clustering identified a subset of neurons with ramping activity. These neurons' firing rates ramped up gradually in single trials over long time scales (up to tens of seconds), were inhibited by rewards, and were better described as being generated by a continuous ramp rather than a discrete stepping process. Together, these results identify reward integration via a continuous ramping process in frontal cortex as a likely candidate for the mechanism by which the mammalian brain solves patch foraging problems.
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Affiliation(s)
- Michael Bukwich
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138
- Center for Brain Science, Harvard University, Cambridge, MA, 02138
- Current address: Sainsbury Wellcome Centre, University College London, London, W1T 4JG, UK
| | - Malcolm G Campbell
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138
- Center for Brain Science, Harvard University, Cambridge, MA, 02138
| | - David Zoltowski
- Department of Statistics, Stanford University, Stanford, CA, 94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94305
| | - Lyle Kingsbury
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138
- Center for Brain Science, Harvard University, Cambridge, MA, 02138
| | - Momchil S Tomov
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138
- Center for Brain Science, Harvard University, Cambridge, MA, 02138
- Current address: Motional AD LLC, Boston, MA 02210
| | - Joshua Stern
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138
- Center for Brain Science, Harvard University, Cambridge, MA, 02138
| | - HyungGoo R Kim
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138
- Center for Brain Science, Harvard University, Cambridge, MA, 02138
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16419, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Jan Drugowitsch
- Department of Neurobiology, Harvard Medical School, Boston, MA, 02115
| | - Scott W Linderman
- Department of Statistics, Stanford University, Stanford, CA, 94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94305
| | - Naoshige Uchida
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, 02138
- Center for Brain Science, Harvard University, Cambridge, MA, 02138
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Jacobs EAK, Ryu S. Larval zebrafish as a model for studying individual variability in translational neuroscience research. Front Behav Neurosci 2023; 17:1143391. [PMID: 37424749 PMCID: PMC10328419 DOI: 10.3389/fnbeh.2023.1143391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/22/2023] [Indexed: 07/11/2023] Open
Abstract
The larval zebrafish is a popular model for translational research into neurological and psychiatric disorders due to its conserved vertebrate brain structures, ease of genetic and experimental manipulation and small size and scalability to large numbers. The possibility of obtaining in vivo whole-brain cellular resolution neural data is contributing important advances into our understanding of neural circuit function and their relation to behavior. Here we argue that the larval zebrafish is ideally poised to push our understanding of how neural circuit function relates to behavior to the next level by including considerations of individual differences. Understanding variability across individuals is particularly relevant for tackling the variable presentations that neuropsychiatric conditions frequently show, and it is equally elemental if we are to achieve personalized medicine in the future. We provide a blueprint for investigating variability by covering examples from humans and other model organisms as well as existing examples from larval zebrafish. We highlight recent studies where variability may be hiding in plain sight and suggest how future studies can take advantage of existing paradigms for further exploring individual variability. We conclude with an outlook on how the field can harness the unique strengths of the zebrafish model to advance this important impending translational question.
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Affiliation(s)
- Elina A. K. Jacobs
- Institute of Human Genetics, University Medical Center of Johannes Gutenberg University Mainz, Mainz, Germany
| | - Soojin Ryu
- Institute of Human Genetics, University Medical Center of Johannes Gutenberg University Mainz, Mainz, Germany
- Living Systems Institute, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
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25
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Voloh B, Eisenreich BR, Maisson DJN, Ebitz RB, Park HS, Hayden BY, Zimmermann J. Hierarchical organization of rhesus macaque behavior. OXFORD OPEN NEUROSCIENCE 2023; 2:kvad006. [PMID: 37577290 PMCID: PMC10421634 DOI: 10.1093/oons/kvad006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/11/2023] [Accepted: 06/12/2023] [Indexed: 08/15/2023]
Abstract
Primatologists, psychologists and neuroscientists have long hypothesized that primate behavior is highly structured. However, delineating that structure has been impossible due to the difficulties of precision behavioral tracking. Here we analyzed a dataset consisting of continuous measures of the 3D position of two male rhesus macaques (Macaca mulatta) performing three different tasks in a large unrestrained environment over several hours. Using an unsupervised embedding approach on the tracked joints, we identified commonly repeated pose patterns, which we call postures. We found that macaques' behavior is characterized by 49 distinct postures, lasting an average of 0.6 seconds. We found evidence that behavior is hierarchically organized, in that transitions between poses tend to occur within larger modules, which correspond to identifiable actions; these actions are further organized hierarchically. Our behavioral decomposition allows us to identify universal (cross-individual and cross-task) and unique (specific to each individual and task) principles of behavior. These results demonstrate the hierarchical nature of primate behavior, provide a method for the automated ethogramming of primate behavior, and provide important constraints on neural models of pose generation.
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Affiliation(s)
- Benjamin Voloh
- Department of Neuroscience, Center for Magnetic Resonance Research, Center for Neuroengineering, 1 Baylor Plaza, Houston, TX 77030
| | - Benjamin R Eisenreich
- Department of Neuroscience, Center for Magnetic Resonance Research, Center for Neuroengineering, 1 Baylor Plaza, Houston, TX 77030
| | - David J-N Maisson
- Department of Neuroscience, Center for Magnetic Resonance Research, Center for Neuroengineering, 1 Baylor Plaza, Houston, TX 77030
| | - R Becket Ebitz
- Department of Neuroscience, Center for Magnetic Resonance Research, Center for Neuroengineering, 1 Baylor Plaza, Houston, TX 77030
| | - Hyun Soo Park
- Department of Computer Science and Engineering, University of Minnesota, 40 Church St, Minneapolis, MN 55455, USA
| | - Benjamin Y Hayden
- Department of Neuroscience, Center for Magnetic Resonance Research, Center for Neuroengineering, 1 Baylor Plaza, Houston, TX 77030
| | - Jan Zimmermann
- Department of Neuroscience, Center for Magnetic Resonance Research, Center for Neuroengineering, 1 Baylor Plaza, Houston, TX 77030
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26
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Dag U, Nwabudike I, Kang D, Gomes MA, Kim J, Atanas AA, Bueno E, Estrem C, Pugliese S, Wang Z, Towlson E, Flavell SW. Dissecting the functional organization of the C. elegans serotonergic system at whole-brain scale. Cell 2023; 186:2574-2592.e20. [PMID: 37192620 PMCID: PMC10484565 DOI: 10.1016/j.cell.2023.04.023] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 03/07/2023] [Accepted: 04/17/2023] [Indexed: 05/18/2023]
Abstract
Serotonin influences many aspects of animal behavior. But how serotonin acts on its diverse receptors across the brain to modulate global activity and behavior is unknown. Here, we examine how serotonin release in C. elegans alters brain-wide activity to induce foraging behaviors, like slow locomotion and increased feeding. Comprehensive genetic analyses identify three core serotonin receptors (MOD-1, SER-4, and LGC-50) that induce slow locomotion upon serotonin release and others (SER-1, SER-5, and SER-7) that interact with them to modulate this behavior. SER-4 induces behavioral responses to sudden increases in serotonin release, whereas MOD-1 induces responses to persistent release. Whole-brain imaging reveals widespread serotonin-associated brain dynamics, spanning many behavioral networks. We map all sites of serotonin receptor expression in the connectome, which, together with synaptic connectivity, helps predict which neurons show serotonin-associated activity. These results reveal how serotonin acts at defined sites across a connectome to modulate brain-wide activity and behavior.
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Affiliation(s)
- Ugur Dag
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ijeoma Nwabudike
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Di Kang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Matthew A Gomes
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungsoo Kim
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Adam A Atanas
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Bueno
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cassi Estrem
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sarah Pugliese
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ziyu Wang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Emma Towlson
- Department of Computer Science, Department of Physics and Astronomy, Hotchkiss Brain Institute, Alberta Children's Research Hospital, University of Calgary, Calgary, AB, Canada
| | - Steven W Flavell
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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27
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Ji P, Wang Y, Peron T, Li C, Nagler J, Du J. Structure and function in artificial, zebrafish and human neural networks. Phys Life Rev 2023; 45:74-111. [PMID: 37182376 DOI: 10.1016/j.plrev.2023.04.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 04/20/2023] [Indexed: 05/16/2023]
Abstract
Network science provides a set of tools for the characterization of the structure and functional behavior of complex systems. Yet a major problem is to quantify how the structural domain is related to the dynamical one. In other words, how the diversity of dynamical states of a system can be predicted from the static network structure? Or the reverse problem: starting from a set of signals derived from experimental recordings, how can one discover the network connections or the causal relations behind the observed dynamics? Despite the advances achieved over the last two decades, many challenges remain concerning the study of the structure-dynamics interplay of complex systems. In neuroscience, progress is typically constrained by the low spatio-temporal resolution of experiments and by the lack of a universal inferring framework for empirical systems. To address these issues, applications of network science and artificial intelligence to neural data have been rapidly growing. In this article, we review important recent applications of methods from those fields to the study of the interplay between structure and functional dynamics of human and zebrafish brain. We cover the selection of topological features for the characterization of brain networks, inference of functional connections, dynamical modeling, and close with applications to both the human and zebrafish brain. This review is intended to neuroscientists who want to become acquainted with techniques from network science, as well as to researchers from the latter field who are interested in exploring novel application scenarios in neuroscience.
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Affiliation(s)
- Peng Ji
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Shanghai 200433, China; MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Yufan Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 320 Yue-Yang Road, Shanghai 200031, China
| | - Thomas Peron
- Institute of Mathematics and Computer Science, University of São Paulo, São Carlos 13566-590, São Paulo, Brazil.
| | - Chunhe Li
- Shanghai Center for Mathematical Sciences and School of Mathematical Sciences, Fudan University, Shanghai 200433, China; Institute of Science and Technology for Brain-Inspired Intelligence and MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China.
| | - Jan Nagler
- Deep Dynamics, Frankfurt School of Finance & Management, Frankfurt, Germany; Centre for Human and Machine Intelligence, Frankfurt School of Finance & Management, Frankfurt, Germany
| | - Jiulin Du
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, 320 Yue-Yang Road, Shanghai 200031, China.
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28
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Hasani H, Sun J, Zhu SI, Rong Q, Willomitzer F, Amor R, McConnell G, Cossairt O, Goodhill GJ. Whole-brain imaging of freely-moving zebrafish. Front Neurosci 2023; 17:1127574. [PMID: 37139528 PMCID: PMC10150962 DOI: 10.3389/fnins.2023.1127574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/28/2023] [Indexed: 05/05/2023] Open
Abstract
One of the holy grails of neuroscience is to record the activity of every neuron in the brain while an animal moves freely and performs complex behavioral tasks. While important steps forward have been taken recently in large-scale neural recording in rodent models, single neuron resolution across the entire mammalian brain remains elusive. In contrast the larval zebrafish offers great promise in this regard. Zebrafish are a vertebrate model with substantial homology to the mammalian brain, but their transparency allows whole-brain recordings of genetically-encoded fluorescent indicators at single-neuron resolution using optical microscopy techniques. Furthermore zebrafish begin to show a complex repertoire of natural behavior from an early age, including hunting small, fast-moving prey using visual cues. Until recently work to address the neural bases of these behaviors mostly relied on assays where the fish was immobilized under the microscope objective, and stimuli such as prey were presented virtually. However significant progress has recently been made in developing brain imaging techniques for zebrafish which are not immobilized. Here we discuss recent advances, focusing particularly on techniques based on light-field microscopy. We also draw attention to several important outstanding issues which remain to be addressed to increase the ecological validity of the results obtained.
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Affiliation(s)
- Hamid Hasani
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
| | - Jipeng Sun
- Department of Computer Science, Northwestern University, Evanston, IL, United States
| | - Shuyu I. Zhu
- Departments of Developmental Biology and Neuroscience, Washington University in St. Louis, St. Louis, MO, United States
| | - Qiangzhou Rong
- Departments of Developmental Biology and Neuroscience, Washington University in St. Louis, St. Louis, MO, United States
| | - Florian Willomitzer
- Wyant College of Optical Sciences, University of Arizona, Tucson, AZ, United States
| | - Rumelo Amor
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Gail McConnell
- Centre for Biophotonics, Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, United Kingdom
| | - Oliver Cossairt
- Department of Computer Science, Northwestern University, Evanston, IL, United States
| | - Geoffrey J. Goodhill
- Departments of Developmental Biology and Neuroscience, Washington University in St. Louis, St. Louis, MO, United States
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29
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Zylbertal A, Bianco IH. Recurrent network interactions explain tectal response variability and experience-dependent behavior. eLife 2023; 12:78381. [PMID: 36943029 PMCID: PMC10030118 DOI: 10.7554/elife.78381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 03/09/2023] [Indexed: 03/23/2023] Open
Abstract
Response variability is an essential and universal feature of sensory processing and behavior. It arises from fluctuations in the internal state of the brain, which modulate how sensory information is represented and transformed to guide behavioral actions. In part, brain state is shaped by recent network activity, fed back through recurrent connections to modulate neuronal excitability. However, the degree to which these interactions influence response variability and the spatial and temporal scales across which they operate, are poorly understood. Here, we combined population recordings and modeling to gain insights into how neuronal activity modulates network state and thereby impacts visually evoked activity and behavior. First, we performed cellular-resolution calcium imaging of the optic tectum to monitor ongoing activity, the pattern of which is both a cause and consequence of changes in network state. We developed a minimal network model incorporating fast, short range, recurrent excitation and long-lasting, activity-dependent suppression that reproduced a hallmark property of tectal activity - intermittent bursting. We next used the model to estimate the excitability state of tectal neurons based on recent activity history and found that this explained a portion of the trial-to-trial variability in visually evoked responses, as well as spatially selective response adaptation. Moreover, these dynamics also predicted behavioral trends such as selective habituation of visually evoked prey-catching. Overall, we demonstrate that a simple recurrent interaction motif can be used to estimate the effect of activity upon the incidental state of a neural network and account for experience-dependent effects on sensory encoding and visually guided behavior.
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Affiliation(s)
- Asaph Zylbertal
- Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom
| | - Isaac H Bianco
- Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom
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30
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The Role of α-Synuclein in the Regulation of Serotonin System: Physiological and Pathological Features. Biomedicines 2023; 11:biomedicines11020541. [PMID: 36831077 PMCID: PMC9953742 DOI: 10.3390/biomedicines11020541] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 01/30/2023] [Accepted: 02/09/2023] [Indexed: 02/16/2023] Open
Abstract
In patients affected by Parkinson's disease (PD), up to 50% of them experience cognitive changes, and psychiatric disturbances, such as anxiety and depression, often precede the onset of motor symptoms and have a negative impact on their quality of life. Pathologically, PD is characterized by the loss of dopamine (DA) neurons in the substantia nigra pars compacta (SNc) and the presence of intracellular inclusions, called Lewy bodies and Lewy neurites, composed mostly of α-synuclein (α-Syn). Much of PD research has focused on the role of α-Syn aggregates in the degeneration of SNc DA neurons due to the impact of striatal DA deficits on classical motor phenotypes. However, abundant Lewy pathology is also found in other brain regions including the midbrain raphe nuclei, which may contribute to non-motor symptoms. Indeed, dysfunction of the serotonergic (5-HT) system, which regulates mood and emotional pathways, occurs during the premotor phase of PD. However, little is known about the functional consequences of α-Syn inclusions in this neuronal population other than DA neurons. Here, we provide an overview of the current knowledge of α-Syn and its role in regulating the 5-HT function in health and disease. Understanding the relative contributions to α-Syn-linked alterations in the 5-HT system may provide a basis for identifying PD patients at risk for developing depression and could lead to a more targeted therapeutic approach.
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31
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Zhu SI, Goodhill GJ. From perception to behavior: The neural circuits underlying prey hunting in larval zebrafish. Front Neural Circuits 2023; 17:1087993. [PMID: 36817645 PMCID: PMC9928868 DOI: 10.3389/fncir.2023.1087993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/10/2023] [Indexed: 02/04/2023] Open
Abstract
A key challenge for neural systems is to extract relevant information from the environment and make appropriate behavioral responses. The larval zebrafish offers an exciting opportunity for studying these sensing processes and sensory-motor transformations. Prey hunting is an instinctual behavior of zebrafish that requires the brain to extract and combine different attributes of the sensory input and form appropriate motor outputs. Due to its small size and transparency the larval zebrafish brain allows optical recording of whole-brain activity to reveal the neural mechanisms involved in prey hunting and capture. In this review we discuss how the larval zebrafish brain processes visual information to identify and locate prey, the neural circuits governing the generation of motor commands in response to prey, how hunting behavior can be modulated by internal states and experience, and some outstanding questions for the field.
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Affiliation(s)
- Shuyu I. Zhu
- Departments of Developmental Biology and Neuroscience, Washington University in St. Louis, St. Louis, MO, United States
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32
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Thivierge JP, Giraud É, Lynn M. Toward a Brain-Inspired Theory of Artificial Learning. Cognit Comput 2023. [DOI: 10.1007/s12559-023-10121-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
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33
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Dag U, Nwabudike I, Kang D, Gomes MA, Kim J, Atanas AA, Bueno E, Estrem C, Pugliese S, Wang Z, Towlson E, Flavell SW. Dissecting the Functional Organization of the C. elegans Serotonergic System at Whole-Brain Scale. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.15.524132. [PMID: 36711891 PMCID: PMC9882198 DOI: 10.1101/2023.01.15.524132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Serotonin controls many aspects of animal behavior and cognition. But how serotonin acts on its diverse receptor types in neurons across the brain to modulate global activity and behavior is unknown. Here, we examine how serotonin release from a feeding-responsive neuron in C. elegans alters brain-wide activity to induce foraging behaviors, like slow locomotion and increased feeding. A comprehensive genetic analysis identifies three core serotonin receptors that collectively induce slow locomotion upon serotonin release and three others that interact with them to further modulate this behavior. The core receptors have different functional roles: some induce behavioral responses to sudden increases in serotonin release, whereas others induce responses to persistent release. Whole-brain calcium imaging reveals widespread serotonin-associated brain dynamics, impacting different behavioral networks in different ways. We map out all sites of serotonin receptor expression in the connectome, which, together with synaptic connectivity, helps predict serotonin-associated brain-wide activity changes. These results provide a global view of how serotonin acts at defined sites across a connectome to modulate brain-wide activity and behavior.
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Affiliation(s)
- Ugur Dag
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,These authors contributed equally to this work
| | - Ijeoma Nwabudike
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,These authors contributed equally to this work
| | - Di Kang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,These authors contributed equally to this work
| | - Matthew A. Gomes
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungsoo Kim
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Adam A. Atanas
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Bueno
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cassi Estrem
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sarah Pugliese
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ziyu Wang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Emma Towlson
- Department of Computer Science, Department of Physics and Astronomy, Hotchkiss Brain Institute, Alberta Children’s Research Hospital, University of Calgary, Calgary, Alberta, Canada
| | - Steven W. Flavell
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,Corresponding Author:
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34
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van der Plas TL, Tubiana J, Le Goc G, Migault G, Kunst M, Baier H, Bormuth V, Englitz B, Debrégeas G. Neural assemblies uncovered by generative modeling explain whole-brain activity statistics and reflect structural connectivity. eLife 2023; 12:83139. [PMID: 36648065 PMCID: PMC9940913 DOI: 10.7554/elife.83139] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 01/15/2023] [Indexed: 01/18/2023] Open
Abstract
Patterns of endogenous activity in the brain reflect a stochastic exploration of the neuronal state space that is constrained by the underlying assembly organization of neurons. Yet, it remains to be shown that this interplay between neurons and their assembly dynamics indeed suffices to generate whole-brain data statistics. Here, we recorded the activity from ∼40,000 neurons simultaneously in zebrafish larvae, and show that a data-driven generative model of neuron-assembly interactions can accurately reproduce the mean activity and pairwise correlation statistics of their spontaneous activity. This model, the compositional Restricted Boltzmann Machine (cRBM), unveils ∼200 neural assemblies, which compose neurophysiological circuits and whose various combinations form successive brain states. We then performed in silico perturbation experiments to determine the interregional functional connectivity, which is conserved across individual animals and correlates well with structural connectivity. Our results showcase how cRBMs can capture the coarse-grained organization of the zebrafish brain. Notably, this generative model can readily be deployed to parse neural data obtained by other large-scale recording techniques.
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Affiliation(s)
- Thijs L van der Plas
- Computational Neuroscience Lab, Department of Neurophysiology, Donders Center for Neuroscience, Radboud UniversityNijmegenNetherlands
- Sorbonne Université, CNRS, Institut de Biologie Paris-Seine (IBPS), Laboratoire Jean Perrin (LJP)ParisFrance
- Department of Physiology, Anatomy and Genetics, University of OxfordOxfordUnited Kingdom
| | - Jérôme Tubiana
- Blavatnik School of Computer Science, Tel Aviv UniversityTel AvivIsrael
| | - Guillaume Le Goc
- Sorbonne Université, CNRS, Institut de Biologie Paris-Seine (IBPS), Laboratoire Jean Perrin (LJP)ParisFrance
| | - Geoffrey Migault
- Sorbonne Université, CNRS, Institut de Biologie Paris-Seine (IBPS), Laboratoire Jean Perrin (LJP)ParisFrance
| | - Michael Kunst
- Department Genes – Circuits – Behavior, Max Planck Institute for Biological IntelligenceMartinsriedGermany
- Allen Institute for Brain ScienceSeattleUnited States
| | - Herwig Baier
- Department Genes – Circuits – Behavior, Max Planck Institute for Biological IntelligenceMartinsriedGermany
| | - Volker Bormuth
- Sorbonne Université, CNRS, Institut de Biologie Paris-Seine (IBPS), Laboratoire Jean Perrin (LJP)ParisFrance
| | - Bernhard Englitz
- Computational Neuroscience Lab, Department of Neurophysiology, Donders Center for Neuroscience, Radboud UniversityNijmegenNetherlands
| | - Georges Debrégeas
- Sorbonne Université, CNRS, Institut de Biologie Paris-Seine (IBPS), Laboratoire Jean Perrin (LJP)ParisFrance
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35
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Yang E, Zwart MF, James B, Rubinov M, Wei Z, Narayan S, Vladimirov N, Mensh BD, Fitzgerald JE, Ahrens MB. A brainstem integrator for self-location memory and positional homeostasis in zebrafish. Cell 2022; 185:5011-5027.e20. [PMID: 36563666 DOI: 10.1016/j.cell.2022.11.022] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/28/2022] [Accepted: 11/21/2022] [Indexed: 12/24/2022]
Abstract
To track and control self-location, animals integrate their movements through space. Representations of self-location are observed in the mammalian hippocampal formation, but it is unknown if positional representations exist in more ancient brain regions, how they arise from integrated self-motion, and by what pathways they control locomotion. Here, in a head-fixed, fictive-swimming, virtual-reality preparation, we exposed larval zebrafish to a variety of involuntary displacements. They tracked these displacements and, many seconds later, moved toward their earlier location through corrective swimming ("positional homeostasis"). Whole-brain functional imaging revealed a network in the medulla that stores a memory of location and induces an error signal in the inferior olive to drive future corrective swimming. Optogenetically manipulating medullary integrator cells evoked displacement-memory behavior. Ablating them, or downstream olivary neurons, abolished displacement corrections. These results reveal a multiregional hindbrain circuit in vertebrates that integrates self-motion and stores self-location to control locomotor behavior.
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Affiliation(s)
- En Yang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
| | - Maarten F Zwart
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; School of Psychology and Neuroscience, Centre for Biophotonics, University of St Andrews, St. Andrews, UK
| | - Ben James
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Mikail Rubinov
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Ziqiang Wei
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Sujatha Narayan
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Nikita Vladimirov
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA; URPP Adaptive Brain Circuits in Development and Learning (AdaBD), University of Zurich, Zurich, Switzerland
| | - Brett D Mensh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - James E Fitzgerald
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA
| | - Misha B Ahrens
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
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36
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Thomson EE, Harfouche M, Kim K, Konda PC, Seitz CW, Cooke C, Xu S, Jacobs WS, Blazing R, Chen Y, Sharma S, Dunn TW, Park J, Horstmeyer RW, Naumann EA. Gigapixel imaging with a novel multi-camera array microscope. eLife 2022; 11:e74988. [PMID: 36515989 PMCID: PMC9917455 DOI: 10.7554/elife.74988] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 11/23/2022] [Indexed: 12/15/2022] Open
Abstract
The dynamics of living organisms are organized across many spatial scales. However, current cost-effective imaging systems can measure only a subset of these scales at once. We have created a scalable multi-camera array microscope (MCAM) that enables comprehensive high-resolution recording from multiple spatial scales simultaneously, ranging from structures that approach the cellular scale to large-group behavioral dynamics. By collecting data from up to 96 cameras, we computationally generate gigapixel-scale images and movies with a field of view over hundreds of square centimeters at an optical resolution of 18 µm. This allows us to observe the behavior and fine anatomical features of numerous freely moving model organisms on multiple spatial scales, including larval zebrafish, fruit flies, nematodes, carpenter ants, and slime mold. Further, the MCAM architecture allows stereoscopic tracking of the z-position of organisms using the overlapping field of view from adjacent cameras. Overall, by removing the bottlenecks imposed by single-camera image acquisition systems, the MCAM provides a powerful platform for investigating detailed biological features and behavioral processes of small model organisms across a wide range of spatial scales.
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Affiliation(s)
- Eric E Thomson
- Department of Neurobiology, Duke School of MedicineDurhamUnited States
| | | | - Kanghyun Kim
- Biomedical Engineering, Duke UniversityDurhamUnited States
| | - Pavan C Konda
- Biomedical Engineering, Duke UniversityDurhamUnited States
| | - Catherine W Seitz
- Department of Neurobiology, Duke School of MedicineDurhamUnited States
| | - Colin Cooke
- Biomedical Engineering, Duke UniversityDurhamUnited States
| | - Shiqi Xu
- Biomedical Engineering, Duke UniversityDurhamUnited States
| | - Whitney S Jacobs
- Department of Neurobiology, Duke School of MedicineDurhamUnited States
| | - Robin Blazing
- Department of Neurobiology, Duke School of MedicineDurhamUnited States
| | - Yang Chen
- Department of Neurobiology, Duke School of MedicineDurhamUnited States
| | | | - Timothy W Dunn
- Biomedical Engineering, Duke UniversityDurhamUnited States
| | | | - Roarke W Horstmeyer
- Ramona Optics IncDurhamUnited States
- Biomedical Engineering, Duke UniversityDurhamUnited States
| | - Eva A Naumann
- Department of Neurobiology, Duke School of MedicineDurhamUnited States
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37
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Shoenhard H, Jain RA, Granato M. The calcium-sensing receptor (CaSR) regulates zebrafish sensorimotor decision making via a genetically defined cluster of hindbrain neurons. Cell Rep 2022; 41:111790. [PMID: 36476852 PMCID: PMC9813870 DOI: 10.1016/j.celrep.2022.111790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 09/21/2022] [Accepted: 11/15/2022] [Indexed: 12/12/2022] Open
Abstract
Decision making is a fundamental nervous system function that ranges widely in complexity and speed of execution. We previously established larval zebrafish as a model for sensorimotor decision making and identified the G-protein-coupled calcium-sensing receptor (CaSR) to be critical for this process. Here, we report that CaSR functions in neurons to dynamically regulate the bias between two behavioral outcomes: escapes and reorientations. By employing a computational guided transgenic strategy, we identify a genetically defined neuronal cluster in the hindbrain as a key candidate site for CaSR function. Finally, we demonstrate that transgenic CaSR expression targeting this cluster consisting of a few hundred neurons shifts behavioral bias in wild-type animals and restores decision making deficits in CaSR mutants. Combined, our data provide a rare example of a G-protein-coupled receptor that biases vertebrate sensorimotor decision making via a defined neuronal cluster.
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Affiliation(s)
- Hannah Shoenhard
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Roshan A. Jain
- Department of Biology, Haverford College, Haverford, PA 19041, USA
| | - Michael Granato
- Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA,Lead contact,Correspondence:
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38
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Magnus G, Xing J, Zhang Y, Han VZ. Diversity of cellular physiology and morphology of Purkinje cells in the adult zebrafish cerebellum. J Comp Neurol 2022; 531:461-485. [PMID: 36453181 DOI: 10.1002/cne.25435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 10/31/2022] [Accepted: 11/04/2022] [Indexed: 12/04/2022]
Abstract
This study was designed to explore the functional circuitry of the adult zebrafish cerebellum, focusing on its Purkinje cells and using whole-cell patch recordings and single cell labeling in slice preparations. Following physiological characterizations, the recorded single cells were labeled for morphological identification. It was found that the zebrafish Purkinje cells are surprisingly diverse. Based on their physiology and morphology, they can be classified into at least three subtypes: Type I, a narrow spike cell, which fires only narrow Na+ spikes (<3 ms in duration), and has a single primary dendrite with an arbor restricted to the distal molecular layer; Type II, a broad spike cell, which fires broad Ca2+ spikes (5-7 ms in duration) and has a primary dendrite with limited branching in the inner molecular layer and then further radiates throughout the molecular layer; and Type III, a very broad spike cell, which fires very broad Ca2+ spikes (≥10 ms in duration) and has a dense proximal dendritic arbor that is either restricted to the inner molecular layer (Type IIIa), or radiates throughout the entire molecular layer (Type IIIb). The graded paired-pulse facilitation of these Purkinje cells' responses to parallel fiber activations and the all-or-none, paired-pulse depression of climbing fiber activation are largely similar to those reported for mammals. The labeled axon terminals of these Purkinje cells end locally, as reported for larval zebrafish. The present study provides evidence that the corresponding functional circuitry and information processing differ from what has been well-established in the mammalian cerebellum.
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Affiliation(s)
- Gerhard Magnus
- Department of Biology University of Washington Seattle Washington USA
- Center for Integrative Brain Research Seattle Children's Research Institute Seattle Washington USA
| | - Junling Xing
- Department of Pediatrics and Neuroscience Xijing Hospital Xi'an China
| | - Yueping Zhang
- Center for Integrative Brain Research Seattle Children's Research Institute Seattle Washington USA
- Department of Pediatrics and Neuroscience Xijing Hospital Xi'an China
| | - Victor Z. Han
- Department of Biology University of Washington Seattle Washington USA
- Center for Integrative Brain Research Seattle Children's Research Institute Seattle Washington USA
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39
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Luo J, Sun C, Chang B, Jing Y, Li K, Li Y, Zhang Q, Wang H, Hou C. MXene-Enabled Self-Adaptive Hydrogel Interface for Active Electroencephalogram Interactions. ACS NANO 2022; 16:19373-19384. [PMID: 36279105 DOI: 10.1021/acsnano.2c08961] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Human-machine interaction plays a significant role in promoting convenience, production efficiency, and usage experience. Because of the universality and characteristics of electroencephalogram (EEG) signals, active EEG interaction is a promising and cutting-edge method for human-machine interaction. The seamless, skin-compliant, and motion-robust human-machine interface (HMI) for active EEG interaction has been in focus. Herein, we report a self-adaptive HMI (PAAS-MXene hydrogel) that can activate rapid gelation (5 s) using MXene cross-linking and conformably self-adapt to the scalp to help improve signal transduction. In addition to exhibiting satisfactory skin compliance, appropriate adhesion, and good biocompatibility, PAAS-MXene has demonstrated electrical performance reliability, such as low impedance (<50 Ω) at physiologically relevant frequencies, stable polarization potential (the rate of change is less than 6.5 × 10-4 V/min), negligible ion conductivity, and impedance change after 1000 stretch cycles, thereby realizing acquisition of EEG signals. In addition, a cap-free EEG signal acquisition method based on PAAS-MXene has been proposed. These findings confirm the high-precision detection ability of PAAS-MXene for electrocardiogram signals and EEG signals. Therefore, PAAS-MXene offers an option to actively control intention, motion, and vision through active EEG signals.
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Affiliation(s)
- Jiabei Luo
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, People's Republis of China
| | - Chuanyue Sun
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, People's Republis of China
| | - Boya Chang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, People's Republis of China
| | - Yangmin Jing
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, People's Republis of China
| | - Kerui Li
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, People's Republis of China
| | - Yaogang Li
- Engineering Research Center of Advanced Glasses Manufacturing Technology, Ministry of Education, Donghua University, Shanghai 201620, People's Republis of China
| | - Qinghong Zhang
- Engineering Research Center of Advanced Glasses Manufacturing Technology, Ministry of Education, Donghua University, Shanghai 201620, People's Republis of China
| | - Hongzhi Wang
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, People's Republis of China
| | - Chengyi Hou
- State Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai 201620, People's Republis of China
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Ye H, Hendee J, Ruan J, Zhirova A, Ye J, Dima M. Neuron matters: neuromodulation with electromagnetic stimulation must consider neurons as dynamic identities. J Neuroeng Rehabil 2022; 19:116. [PMID: 36329492 PMCID: PMC9632094 DOI: 10.1186/s12984-022-01094-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 10/15/2022] [Indexed: 11/06/2022] Open
Abstract
Neuromodulation with electromagnetic stimulation is widely used for the control of abnormal neural activity, and has been proven to be a valuable alternative to pharmacological tools for the treatment of many neurological diseases. Tremendous efforts have been focused on the design of the stimulation apparatus (i.e., electrodes and magnetic coils) that delivers the electric current to the neural tissue, and the optimization of the stimulation parameters. Less attention has been given to the complicated, dynamic properties of the neurons, and their context-dependent impact on the stimulation effects. This review focuses on the neuronal factors that influence the outcomes of electromagnetic stimulation in neuromodulation. Evidence from multiple levels (tissue, cellular, and single ion channel) are reviewed. Properties of the neural elements and their dynamic changes play a significant role in the outcome of electromagnetic stimulation. This angle of understanding yields a comprehensive perspective of neural activity during electrical neuromodulation, and provides insights in the design and development of novel stimulation technology.
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Affiliation(s)
- Hui Ye
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Jenna Hendee
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Joyce Ruan
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Alena Zhirova
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Jayden Ye
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
| | - Maria Dima
- grid.164971.c0000 0001 1089 6558Department of Biology, Quinlan Life Sciences Education and Research Center, Loyola University Chicago, 1032 W. Sheridan Rd., Chicago, IL 60660 USA
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41
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Post RJ, Bulkin DA, Ebitz RB, Lee V, Han K, Warden MR. Tonic activity in lateral habenula neurons acts as a neutral valence brake on reward-seeking behavior. Curr Biol 2022; 32:4325-4336.e5. [PMID: 36049479 PMCID: PMC9613558 DOI: 10.1016/j.cub.2022.08.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 12/16/2021] [Accepted: 08/09/2022] [Indexed: 11/16/2022]
Abstract
Survival requires both the ability to persistently pursue goals and the ability to determine when it is time to stop, an adaptive balance of perseverance and disengagement. Neural activity in the lateral habenula (LHb) has been linked to negative valence, but its role in regulating the balance between engaged reward seeking and disengaged behavioral states remains unclear. Here, we show that LHb neural activity is tonically elevated during minutes-long periods of disengagement from reward-seeking behavior, both when due to repeated reward omission (negative valence) and when sufficient reward has been consumed (positive valence). Furthermore, we show that LHb inhibition extends ongoing reward-seeking behavioral states but does not prompt task re-engagement. We find no evidence for similar tonic activity changes in ventral tegmental area dopamine neurons. Our findings support a framework in which tonic activity in LHb neurons suppresses engagement in reward-seeking behavior in response to both negatively and positively valenced factors.
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Affiliation(s)
- Ryan J Post
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA; Cornell Neurotech, Cornell University, Ithaca, NY 14853, USA
| | - David A Bulkin
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA; Cornell Neurotech, Cornell University, Ithaca, NY 14853, USA
| | - R Becket Ebitz
- Department of Neuroscience, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Vladlena Lee
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Kasey Han
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
| | - Melissa R Warden
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA; Cornell Neurotech, Cornell University, Ithaca, NY 14853, USA.
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42
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Blevins AS, Bassett DS, Scott EK, Vanwalleghem GC. From calcium imaging to graph topology. Netw Neurosci 2022; 6:1125-1147. [PMID: 38800465 PMCID: PMC11117109 DOI: 10.1162/netn_a_00262] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 06/13/2022] [Indexed: 05/29/2024] Open
Abstract
Systems neuroscience is facing an ever-growing mountain of data. Recent advances in protein engineering and microscopy have together led to a paradigm shift in neuroscience; using fluorescence, we can now image the activity of every neuron through the whole brain of behaving animals. Even in larger organisms, the number of neurons that we can record simultaneously is increasing exponentially with time. This increase in the dimensionality of the data is being met with an explosion of computational and mathematical methods, each using disparate terminology, distinct approaches, and diverse mathematical concepts. Here we collect, organize, and explain multiple data analysis techniques that have been, or could be, applied to whole-brain imaging, using larval zebrafish as an example model. We begin with methods such as linear regression that are designed to detect relations between two variables. Next, we progress through network science and applied topological methods, which focus on the patterns of relations among many variables. Finally, we highlight the potential of generative models that could provide testable hypotheses on wiring rules and network progression through time, or disease progression. While we use examples of imaging from larval zebrafish, these approaches are suitable for any population-scale neural network modeling, and indeed, to applications beyond systems neuroscience. Computational approaches from network science and applied topology are not limited to larval zebrafish, or even to systems neuroscience, and we therefore conclude with a discussion of how such methods can be applied to diverse problems across the biological sciences.
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Affiliation(s)
- Ann S. Blevins
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S. Bassett
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - Ethan K. Scott
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
- Department of Anatomy and Physiology, School of Biomedical Sciences, University of Melbourne, Parkville, Australia
| | - Gilles C. Vanwalleghem
- Danish Research Institute of Translational Neuroscience (DANDRITE), Nordic EMBL Partnership for Molecular Medicine, Aarhus University, Aarhus, Denmark
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
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43
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Fast, efficient, and accurate neuro-imaging denoising via supervised deep learning. Nat Commun 2022; 13:5165. [PMID: 36056020 PMCID: PMC9440141 DOI: 10.1038/s41467-022-32886-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 08/18/2022] [Indexed: 11/08/2022] Open
Abstract
Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power. While deep-learning methods have recently been applied to denoise images, their applications to downstream analyses, such as recovering high-SNR calcium traces, have been limited. Further, these methods require temporally-sequential pre-registered data acquired at ultrafast rates. Here, we demonstrate a supervised deep-denoising method to circumvent these tradeoffs for several applications, including whole-brain imaging, large-field-of-view imaging in freely moving animals, and recovering complex neurite structures in C. elegans. Our framework has 30× smaller memory footprint, and is fast in training and inference (50–70 ms); it is highly accurate and generalizable, and further, trained with only small, non-temporally-sequential, independently-acquired training datasets (∼500 pairs of images). We envision that the framework will enable faster and long-term imaging experiments necessary to study neuronal mechanisms of many behaviors. Volumetric functional imaging is widely used for recording neuron activities in vivo for many experimental organisms. Here the authors report supervised deep-denoising methods for improved whole-brain imaging, large field-of-view imaging in freely moving animals, and recovering complex neurite structures in C. elegans.
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44
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Wagle M, Zarei M, Lovett-Barron M, Poston KT, Xu J, Ramey V, Pollard KS, Prober DA, Schulkin J, Deisseroth K, Guo S. Brain-wide perception of the emotional valence of light is regulated by distinct hypothalamic neurons. Mol Psychiatry 2022; 27:3777-3793. [PMID: 35484242 PMCID: PMC9613822 DOI: 10.1038/s41380-022-01567-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/25/2022] [Accepted: 04/06/2022] [Indexed: 02/08/2023]
Abstract
Salient sensory stimuli are perceived by the brain, which guides both the timing and outcome of behaviors in a context-dependent manner. Light is such a stimulus, which is used in treating mood disorders often associated with a dysregulated hypothalamic-pituitary-adrenal stress axis. Relationships between the emotional valence of light and the hypothalamus, and how they interact to exert brain-wide impacts remain unclear. Employing larval zebrafish with analogous hypothalamic systems to mammals, we show in free-swimming animals that hypothalamic corticotropin releasing factor (CRFHy) neurons promote dark avoidance, and such role is not shared by other hypothalamic peptidergic neurons. Single-neuron projection analyses uncover processes extended by individual CRFHy neurons to multiple targets including sensorimotor and decision-making areas. In vivo calcium imaging uncovers a complex and heterogeneous response of individual CRFHy neurons to the light or dark stimulus, with a reduced overall sum of CRF neuronal activity in the presence of light. Brain-wide calcium imaging under alternating light/dark stimuli further identifies distinct and distributed photic response neuronal types. CRFHy neuronal ablation increases an overall representation of light in the brain and broadly enhances the functional connectivity associated with an exploratory brain state. These findings delineate brain-wide photic perception, uncover a previously unknown role of CRFHy neurons in regulating the perception and emotional valence of light, and suggest that light therapy may alleviate mood disorders through reducing an overall sum of CRF neuronal activity.
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Affiliation(s)
- Mahendra Wagle
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94143-2811, USA
| | - Mahdi Zarei
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94143-2811, USA
| | - Matthew Lovett-Barron
- Department of Bioengineering, Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
- Neurobiology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Kristina Tyler Poston
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94143-2811, USA
| | - Jin Xu
- Tianqiao and Chrissy Chen Institute for Neuroscience, Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Vince Ramey
- Biophysics Graduate Group, University of California, Berkeley, CA, USA
- Invitae Inc., San Francisco, CA, USA
| | - Katherine S Pollard
- Gladstone Institute of Data Science & Biotechnology, San Francisco, CA, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - David A Prober
- Tianqiao and Chrissy Chen Institute for Neuroscience, Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Jay Schulkin
- Department of Obstetrics & Gynecology, School of Medicine, University of Washington, Seattle, WA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Su Guo
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94143-2811, USA.
- Programs in Human Genetics and Biological Sciences, Kavli Institute of Fundamental Neuroscience, The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, Bakar Aging Research Institute, University of California, San Francisco, CA, 94143-2811, USA.
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Flavell SW, Gogolla N, Lovett-Barron M, Zelikowsky M. The emergence and influence of internal states. Neuron 2022; 110:2545-2570. [PMID: 35643077 PMCID: PMC9391310 DOI: 10.1016/j.neuron.2022.04.030] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 02/11/2022] [Accepted: 04/27/2022] [Indexed: 01/09/2023]
Abstract
Animal behavior is shaped by a variety of "internal states"-partially hidden variables that profoundly shape perception, cognition, and action. The neural basis of internal states, such as fear, arousal, hunger, motivation, aggression, and many others, is a prominent focus of research efforts across animal phyla. Internal states can be inferred from changes in behavior, physiology, and neural dynamics and are characterized by properties such as pleiotropy, persistence, scalability, generalizability, and valence. To date, it remains unclear how internal states and their properties are generated by nervous systems. Here, we review recent progress, which has been driven by advances in behavioral quantification, cellular manipulations, and neural population recordings. We synthesize research implicating defined subsets of state-inducing cell types, widespread changes in neural activity, and neuromodulation in the formation and updating of internal states. In addition to highlighting the significance of these findings, our review advocates for new approaches to clarify the underpinnings of internal brain states across the animal kingdom.
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Affiliation(s)
- Steven W Flavell
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Nadine Gogolla
- Emotion Research Department, Max Planck Institute of Psychiatry, 80804 Munich, Germany; Circuits for Emotion Research Group, Max Planck Institute of Neurobiology, 82152 Martinsried, Germany.
| | - Matthew Lovett-Barron
- Division of Biological Sciences-Neurobiology Section, University of California, San Diego, La Jolla, CA 92093, USA.
| | - Moriel Zelikowsky
- Department of Neurobiology, University of Utah, Salt Lake City, UT 84112, USA.
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46
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Shine JM, O’Callaghan C, Walpola IC, Wainstein G, Taylor N, Aru J, Huebner B, John YJ. Understanding the effects of serotonin in the brain through its role in the gastrointestinal tract. Brain 2022; 145:2967-2981. [DOI: 10.1093/brain/awac256] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 06/12/2022] [Accepted: 06/14/2022] [Indexed: 11/12/2022] Open
Abstract
Abstract
The neuromodulatory arousal system imbues the nervous system with the flexibility and robustness required to facilitate adaptive behaviour. While there are well-understood mechanisms linking dopamine, noradrenaline and acetylcholine to distinct behavioural states, similar conclusions have not been as readily available for serotonin. Fascinatingly, despite clear links between serotonergic function and cognitive capacities as diverse as reward processing, exploration, and the psychedelic experience, over 95% of the serotonin in the body is released in the gastrointestinal tract, where it controls digestive muscle contractions (peristalsis). Here, we argue that framing neural serotonin as a rostral extension of the gastrointestinal serotonergic system dissolves much of the mystery associated with the central serotonergic system. Specifically, we outline that central serotonin activity mimics the effects of a digestion/satiety circuit mediated by hypothalamic control over descending serotonergic nuclei in the brainstem. We review commonalities and differences between these two circuits, with a focus on the heterogeneous expression of different classes of serotonin receptors in the brain. Much in the way that serotonin-induced peristalsis facilitates the work of digestion, serotonergic influences over cognition can be reframed as performing the work of cognition. Extending this analogy, we argue that the central serotonergic system allows the brain to arbitrate between different cognitive modes as a function of serotonergic tone: low activity facilitates cognitive automaticity, whereas higher activity helps to identify flexible solutions to problems, particularly if and when the initial responses fail. This perspective sheds light on otherwise disparate capacities mediated by serotonin, and also helps to understand why there are such pervasive links between serotonergic pathology and the symptoms of psychiatric disorders.
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Affiliation(s)
| | | | - Ishan C Walpola
- Prince of Wales Hospital , Randwick, New South Wales , Australia
| | | | | | - Jaan Aru
- University of Tartu , Tartu , Estonia
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47
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The neuronal logic of how internal states control food choice. Nature 2022; 607:747-755. [DOI: 10.1038/s41586-022-04909-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 05/25/2022] [Indexed: 11/08/2022]
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48
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Tan JXM, Ang RJW, Wee CL. Larval Zebrafish as a Model for Mechanistic Discovery in Mental Health. Front Mol Neurosci 2022; 15:900213. [PMID: 35813062 PMCID: PMC9263853 DOI: 10.3389/fnmol.2022.900213] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 04/25/2022] [Indexed: 12/23/2022] Open
Abstract
Animal models are essential for the discovery of mechanisms and treatments for neuropsychiatric disorders. However, complex mental health disorders such as depression and anxiety are difficult to fully recapitulate in these models. Borrowing from the field of psychiatric genetics, we reiterate the framework of 'endophenotypes' - biological or behavioral markers with cellular, molecular or genetic underpinnings - to reduce complex disorders into measurable behaviors that can be compared across organisms. Zebrafish are popular disease models due to the conserved genetic, physiological and anatomical pathways between zebrafish and humans. Adult zebrafish, which display more sophisticated behaviors and cognition, have long been used to model psychiatric disorders. However, larvae (up to 1 month old) are more numerous and also optically transparent, and hence are particularly suited for high-throughput screening and brain-wide neural circuit imaging. A number of behavioral assays have been developed to quantify neuropsychiatric phenomena in larval zebrafish. Here, we will review these assays and the current knowledge regarding the underlying mechanisms of their behavioral readouts. We will also discuss the existing evidence linking larval zebrafish behavior to specific human behavioral traits and how the endophenotype framework can be applied. Importantly, many of the endophenotypes we review do not solely define a diseased state but could manifest as a spectrum across the general population. As such, we make the case for larval zebrafish as a promising model for extending our understanding of population mental health, and for identifying novel therapeutics and interventions with broad impact.
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Affiliation(s)
| | | | - Caroline Lei Wee
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
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Grün S, Li J, McNaughton B, Petersen C, McCormick D, Robson D, Buzsáki G, Harris K, Sejnowski T, Mrsic-Flogel T, Lindén H, Roland PE. Emerging principles of spacetime in brains: Meeting report on spatial neurodynamics. Neuron 2022; 110:1894-1898. [PMID: 35709696 DOI: 10.1016/j.neuron.2022.05.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 05/01/2022] [Accepted: 05/16/2022] [Indexed: 11/26/2022]
Abstract
How do neurons and networks of neurons interact spatially? Here, we overview recent discoveries revealing how spatial dynamics of spiking and postsynaptic activity efficiently expose and explain fundamental brain and brainstem mechanisms behind detection, perception, learning, and behavior.
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Affiliation(s)
- Sonja Grün
- Institute for Neuroscience and Medicine (INM-6, INM-10) & Institute for Advanced Simulation (IAS-6), Forschungszentrum Jülich GmbH, Jülich, Germany; SystemTheoretical Systems Neurobiology, RWTH Aachen University, Aachen, Germany
| | - Jennifer Li
- Systems Neuroscience and Neuroengineering, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Bruce McNaughton
- Department of Neurobiology and Behavior, University of California Irvine, CA, USA
| | | | - David McCormick
- Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | - Drew Robson
- Systems Neuroscience and Neuroengineering, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - György Buzsáki
- Neuroscience Institute, Langone Medical Center, New York University, New York, NY, USA
| | - Kenneth Harris
- Institute of Neurology, University College London, London, UK
| | | | | | - Henrik Lindén
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
| | - Per E Roland
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.
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50
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Klein-Flügge MC, Bongioanni A, Rushworth MFS. Medial and orbital frontal cortex in decision-making and flexible behavior. Neuron 2022; 110:2743-2770. [PMID: 35705077 DOI: 10.1016/j.neuron.2022.05.022] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/17/2022] [Accepted: 05/19/2022] [Indexed: 11/15/2022]
Abstract
The medial frontal cortex and adjacent orbitofrontal cortex have been the focus of investigations of decision-making, behavioral flexibility, and social behavior. We review studies conducted in humans, macaques, and rodents and argue that several regions with different functional roles can be identified in the dorsal anterior cingulate cortex, perigenual anterior cingulate cortex, anterior medial frontal cortex, ventromedial prefrontal cortex, and medial and lateral parts of the orbitofrontal cortex. There is increasing evidence that the manner in which these areas represent the value of the environment and specific choices is different from subcortical brain regions and more complex than previously thought. Although activity in some regions reflects distributions of reward and opportunities across the environment, in other cases, activity reflects the structural relationships between features of the environment that animals can use to infer what decision to take even if they have not encountered identical opportunities in the past.
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Affiliation(s)
- Miriam C Klein-Flügge
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford OX3 9DU, UK; Department of Psychiatry, University of Oxford, Warneford Lane, Headington, Oxford OX3 7JX, UK.
| | - Alessandro Bongioanni
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford OX3 9DU, UK
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