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Kimchi EY, Burgos-Robles A, Matthews GA, Chakoma T, Patarino M, Weddington JC, Siciliano C, Yang W, Foutch S, Simons R, Fong MF, Jing M, Li Y, Polley DB, Tye KM. Reward contingency gates selective cholinergic suppression of amygdala neurons. eLife 2024; 12:RP89093. [PMID: 38376907 PMCID: PMC10942609 DOI: 10.7554/elife.89093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024] Open
Abstract
Basal forebrain cholinergic neurons modulate how organisms process and respond to environmental stimuli through impacts on arousal, attention, and memory. It is unknown, however, whether basal forebrain cholinergic neurons are directly involved in conditioned behavior, independent of secondary roles in the processing of external stimuli. Using fluorescent imaging, we found that cholinergic neurons are active during behavioral responding for a reward - even prior to reward delivery and in the absence of discrete stimuli. Photostimulation of basal forebrain cholinergic neurons, or their terminals in the basolateral amygdala (BLA), selectively promoted conditioned responding (licking), but not unconditioned behavior nor innate motor outputs. In vivo electrophysiological recordings during cholinergic photostimulation revealed reward-contingency-dependent suppression of BLA neural activity, but not prefrontal cortex. Finally, ex vivo experiments demonstrated that photostimulation of cholinergic terminals suppressed BLA projection neuron activity via monosynaptic muscarinic receptor signaling, while also facilitating firing in BLA GABAergic interneurons. Taken together, we show that the neural and behavioral effects of basal forebrain cholinergic activation are modulated by reward contingency in a target-specific manner.
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Affiliation(s)
- Eyal Y Kimchi
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- Department of Neurology, Northwestern UniversityChicagoUnited States
| | - Anthony Burgos-Robles
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- The Department of Neuroscience, Developmental, and Regenerative Biology, Neuroscience Institute & Brain Health Consortium, University of Texas at San AntonioSan AntonioUnited States
| | - Gillian A Matthews
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Tatenda Chakoma
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Makenzie Patarino
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Javier C Weddington
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Cody Siciliano
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- Vanderbilt Center for Addiction Research, Department of Pharmacology, Vanderbilt UniversityNashvilleUnited States
| | - Wannan Yang
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Shaun Foutch
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Renee Simons
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Ming-fai Fong
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- Coulter Department of Biomedical Engineering, Georgia Tech & Emory UniversityAtlantaUnited States
| | - Miao Jing
- Chinese Institute for Brain ResearchBeijingChina
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences; PKUIDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life SciencesBeijingChina
| | - Daniel B Polley
- Eaton-Peabody Laboratories, Massachusetts Eye and EarBostonUnited States
- Department of Otolaryngology – Head and Neck Surgery, Harvard Medical SchoolBostonUnited States
| | - Kay M Tye
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- HHMI Investigator, Member of the Kavli Institute for Brain and Mind, and Wylie Vale Professor at the Salk Institute for Biological StudiesLa JollaUnited States
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Srinivasan S, Daste S, Modi MN, Turner GC, Fleischmann A, Navlakha S. Effects of stochastic coding on olfactory discrimination in flies and mice. PLoS Biol 2023; 21:e3002206. [PMID: 37906721 PMCID: PMC10618007 DOI: 10.1371/journal.pbio.3002206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 08/21/2023] [Indexed: 11/02/2023] Open
Abstract
Sparse coding can improve discrimination of sensory stimuli by reducing overlap between their representations. Two factors, however, can offset sparse coding's benefits: similar sensory stimuli have significant overlap and responses vary across trials. To elucidate the effects of these 2 factors, we analyzed odor responses in the fly and mouse olfactory regions implicated in learning and discrimination-the mushroom body (MB) and the piriform cortex (PCx). We found that neuronal responses fall along a continuum from extremely reliable across trials to extremely variable or stochastic. Computationally, we show that the observed variability arises from noise within central circuits rather than sensory noise. We propose this coding scheme to be advantageous for coarse- and fine-odor discrimination. More reliable cells enable quick discrimination between dissimilar odors. For similar odors, however, these cells overlap and do not provide distinguishing information. By contrast, more unreliable cells are decorrelated for similar odors, providing distinguishing information, though these benefits only accrue with extended training with more trials. Overall, we have uncovered a conserved, stochastic coding scheme in vertebrates and invertebrates, and we identify a candidate mechanism, based on variability in a winner-take-all (WTA) inhibitory circuit, that improves discrimination with training.
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Affiliation(s)
- Shyam Srinivasan
- Kavli Institute for Brain and Mind, University of California, San Diego, California, United States of America
- Salk Institute for Biological Studies, La Jolla, California, United States of America
| | - Simon Daste
- Department of Neuroscience, Division of Biology and Medicine, Brown University, Providence, Rhode Island, United States of America
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America
| | - Mehrab N. Modi
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Glenn C. Turner
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America
| | - Alexander Fleischmann
- Department of Neuroscience, Division of Biology and Medicine, Brown University, Providence, Rhode Island, United States of America
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown University, Providence, Rhode Island, United States of America
| | - Saket Navlakha
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
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Smith DM, Loughnan R, Friedman NP, Parekh P, Frei O, Thompson WK, Andreassen OA, Neale M, Jernigan TL, Dale AM. Heritability Estimation of Cognitive Phenotypes in the ABCD Study ® Using Mixed Models. Behav Genet 2023; 53:169-188. [PMID: 37024669 PMCID: PMC10154273 DOI: 10.1007/s10519-023-10141-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 03/15/2023] [Indexed: 04/08/2023]
Abstract
Twin and family studies have historically aimed to partition phenotypic variance into components corresponding to additive genetic effects (A), common environment (C), and unique environment (E). Here we present the ACE Model and several extensions in the Adolescent Brain Cognitive Development℠ Study (ABCD Study®), employed using the new Fast Efficient Mixed Effects Analysis (FEMA) package. In the twin sub-sample (n = 924; 462 twin pairs), heritability estimates were similar to those reported by prior studies for height (twin heritability = 0.86) and cognition (twin heritability between 0.00 and 0.61), respectively. Incorporating SNP-derived genetic relatedness and using the full ABCD Study® sample (n = 9,742) led to narrower confidence intervals for all parameter estimates. By leveraging the sparse clustering method used by FEMA to handle genetic relatedness only for participants within families, we were able to take advantage of the diverse distribution of genetic relatedness within the ABCD Study® sample.
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Affiliation(s)
- Diana M Smith
- Neurosciences Graduate Program, University of California San Diego, La Jolla, CA, USA.
- Center for Human Development, University of California, San Diego, La Jolla, CA, USA.
- Center for Multimodal Imaging and Genetics, San Diego School of Medicine, University of California, La Jolla, CA, USA.
| | - Robert Loughnan
- Population Neuroscience and Genetics Lab, University of California, San Diego, La Jolla, CA, USA
| | - Naomi P Friedman
- Institute for Behavioral Genetics, Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Pravesh Parekh
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Wesley K Thompson
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Michael Neale
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Terry L Jernigan
- Center for Human Development, University of California, San Diego, La Jolla, CA, USA
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Anders M Dale
- Center for Multimodal Imaging and Genetics, San Diego School of Medicine, University of California, La Jolla, CA, USA
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
- Department of Radiology, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Department of Neuroscience, University of California, San Diego School of Medicine, La Jolla, CA, USA
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Glavis-Bloom C, Vanderlip CR, Weiser Novak S, Kuwajima M, Kirk L, Harris KM, Manor U, Reynolds JH. Violation of the ultrastructural size principle in the dorsolateral prefrontal cortex underlies working memory impairment in the aged common marmoset (Callithrix jacchus). Front Aging Neurosci 2023; 15:1146245. [PMID: 37122384 PMCID: PMC10132463 DOI: 10.3389/fnagi.2023.1146245] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/21/2023] [Indexed: 05/02/2023] Open
Abstract
Morphology and function of the dorsolateral prefrontal cortex (dlPFC), and corresponding working memory performance, are affected early in the aging process, but nearly half of aged individuals are spared of working memory deficits. Translationally relevant model systems are critical for determining the neurobiological drivers of this variability. The common marmoset (Callithrix jacchus) is advantageous as a model for these investigations because, as a non-human primate, marmosets have a clearly defined dlPFC that enables measurement of prefrontal-dependent cognitive functions, and their short (∼10 year) lifespan facilitates longitudinal studies of aging. Previously, we characterized working memory capacity in a cohort of marmosets that collectively covered the lifespan, and found age-related working memory impairment. We also found a remarkable degree of heterogeneity in performance, similar to that found in humans. Here, we tested the hypothesis that changes to synaptic ultrastructure that affect synaptic efficacy stratify marmosets that age with cognitive impairment from those that age without cognitive impairment. We utilized electron microscopy to visualize synapses in the marmoset dlPFC and measured the sizes of boutons, presynaptic mitochondria, and synapses. We found that coordinated scaling of the sizes of synapses and mitochondria with their associated boutons is essential for intact working memory performance in aged marmosets. Further, lack of synaptic scaling, due to a remarkable failure of synaptic mitochondria to scale with presynaptic boutons, selectively underlies age-related working memory impairment. We posit that this decoupling results in mismatched energy supply and demand, leading to impaired synaptic transmission. We also found that aged marmosets have fewer synapses in dlPFC than young, though the severity of synapse loss did not predict whether aging occurred with or without cognitive impairment. This work identifies a novel mechanism of synapse dysfunction that stratifies marmosets that age with cognitive impairment from those that age without cognitive impairment. The process by which synaptic scaling is regulated is yet unknown and warrants future investigation.
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Affiliation(s)
- Courtney Glavis-Bloom
- Salk Institute for Biological Studies, Systems Neurobiology Laboratory, La Jolla, CA, United States
| | - Casey R. Vanderlip
- Salk Institute for Biological Studies, Systems Neurobiology Laboratory, La Jolla, CA, United States
| | - Sammy Weiser Novak
- Salk Institute for Biological Studies, Waitt Advanced Biophotonics Center, La Jolla, CA, United States
| | - Masaaki Kuwajima
- Department of Neuroscience, Center for Learning and Memory, University of Texas at Austin, Austin, TX, United States
| | - Lyndsey Kirk
- Department of Neuroscience, Center for Learning and Memory, University of Texas at Austin, Austin, TX, United States
| | - Kristen M. Harris
- Department of Neuroscience, Center for Learning and Memory, University of Texas at Austin, Austin, TX, United States
| | - Uri Manor
- Salk Institute for Biological Studies, Waitt Advanced Biophotonics Center, La Jolla, CA, United States
| | - John H. Reynolds
- Salk Institute for Biological Studies, Systems Neurobiology Laboratory, La Jolla, CA, United States
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Porcu A, Nilsson A, Booreddy S, Barnes SA, Welsh DK, Dulcis D. Seasonal changes in day length induce multisynaptic neurotransmitter switching to regulate hypothalamic network activity and behavior. Sci Adv 2022; 8:eabn9867. [PMID: 36054362 PMCID: PMC10848959 DOI: 10.1126/sciadv.abn9867] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 07/19/2022] [Indexed: 05/18/2023]
Abstract
Seasonal changes in day length (photoperiod) affect numerous physiological functions. The suprachiasmatic nucleus (SCN)-paraventricular nucleus (PVN) axis plays a key role in processing photoperiod-related information. Seasonal variations in SCN and PVN neurotransmitter expression have been observed in humans and animal models. However, the molecular mechanisms by which the SCN-PVN network responds to altered photoperiod is unknown. Here, we show in mice that neuromedin S (NMS) and vasoactive intestinal polypeptide (VIP) neurons in the SCN display photoperiod-induced neurotransmitter plasticity. In vivo recording of calcium dynamics revealed that NMS neurons alter PVN network activity in response to winter-like photoperiod. Chronic manipulation of NMS neurons is sufficient to induce neurotransmitter switching in PVN neurons and affects locomotor activity. Our findings reveal previously unidentified molecular adaptations of the SCN-PVN network in response to seasonality and the role for NMS neurons in adjusting hypothalamic function to day length via a coordinated multisynaptic neurotransmitter switching affecting behavior.
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Affiliation(s)
- Alessandra Porcu
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Center for Circadian Biology, University of California San Diego, La Jolla, CA, USA
| | - Anna Nilsson
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Sathwik Booreddy
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Samuel A. Barnes
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - David K. Welsh
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Center for Circadian Biology, University of California San Diego, La Jolla, CA, USA
| | - Davide Dulcis
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Center for Circadian Biology, University of California San Diego, La Jolla, CA, USA
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Lewis JD, O’Reilly C, Bock E, Theilmann RJ, Townsend J. Aging-Related Differences in Structural and Functional Interhemispheric Connectivity. Cereb Cortex 2022; 32:1379-1389. [PMID: 34496021 PMCID: PMC9190305 DOI: 10.1093/cercor/bhab275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 07/18/2021] [Accepted: 07/19/2021] [Indexed: 11/13/2022] Open
Abstract
There is substantial evidence of age-related declines in anatomical connectivity during adulthood, with associated alterations in functional connectivity. But the relation of those functional alterations to the structural reductions is unclear. The complexities of both the structural and the functional connectomes make it difficult to determine such relationships. We pursue this question with methods, based on animal research, that specifically target the interhemispheric connections between the visual cortices. We collect t1- and diffusion-weighted imaging data from which we assess the integrity of the white matter interconnecting the bilateral visual cortices. Functional connectivity between the visual cortices is measured with electroencephalography during the presentation of drifting sinusoidal gratings that agree or conflict across hemifields. Our results show age-related reductions in the integrity of the white matter interconnecting the visual cortices, and age-related increases in the difference in functional interhemispheric lagged coherence between agreeing versus disagreeing visual stimuli. We show that integrity of the white matter in the splenium of the corpus callosum predicts the differences in lagged coherence for the agreeing versus disagreeing stimuli; and that this relationship is mediated by age. These results give new insight into the causal relationship between age and functional connectivity.
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Affiliation(s)
- John D Lewis
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Christian O’Reilly
- Azrieli Centre for Autism Research, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Elizabeth Bock
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, H3A 2B4, Canada
| | | | - Jeanne Townsend
- Department of Neurosciences, UC San Diego, La Jolla, CA 92093, USA
- Research on Aging and Development Laboratory, UC San Diego, La Jolla, CA 92037, USA
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Hwang EJ, Dahlen JE, Hu YY, Aguilar K, Yu B, Mukundan M, Mitani A, Komiyama T. Disengagement of motor cortex from movement control during long-term learning. Sci Adv 2019; 5:eaay0001. [PMID: 31693007 PMCID: PMC6821459 DOI: 10.1126/sciadv.aay0001] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 09/16/2019] [Indexed: 05/14/2023]
Abstract
Motor learning involves reorganization of the primary motor cortex (M1). However, it remains unclear how the involvement of M1 in movement control changes during long-term learning. To address this, we trained mice in a forelimb-based motor task over months and performed optogenetic inactivation and two-photon calcium imaging in M1 during the long-term training. We found that M1 inactivation impaired the forelimb movements in the early and middle stages, but not in the late stage, indicating that the movements that initially required M1 became independent of M1. As previously shown, M1 population activity became more consistent across trials from the early to middle stage while task performance rapidly improved. However, from the middle to late stage, M1 population activity became again variable despite consistent expert behaviors. This later decline in activity consistency suggests dissociation between M1 and movements. These findings suggest that long-term motor learning can disengage M1 from movement control.
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