1. Neuroscience
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In vivo functional diversity of midbrain dopamine neurons within identified axonal projections

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Cite this article as: eLife 2019;8:e48408 doi: 10.7554/eLife.48408

Abstract

Functional diversity of midbrain dopamine (DA) neurons ranges across multiple scales, from differences in intrinsic properties and connectivity to selective task engagement in behaving animals. Distinct in vitro biophysical features of DA neurons have been associated with different axonal projection targets. However, it is unknown how this translates to different firing patterns of projection-defined DA subpopulations in the intact brain. We combined retrograde tracing with single-unit recording and labelling in mouse brain to create an in vivo functional topography of the midbrain DA system. We identified differences in burst firing among DA neurons projecting to dorsolateral striatum. Bursting also differentiated DA neurons in the medial substantia nigra (SN) projecting either to dorsal or ventral striatum. We found differences in mean firing rates and pause durations among ventral tegmental area (VTA) DA neurons projecting to lateral or medial shell of nucleus accumbens. Our data establishes a high-resolution functional in vivo landscape of midbrain DA neurons.

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All data generated or analysed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. Navid Farassat

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  2. ​Kauê Machado Costa

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5562-6495
  3. Strahinja Stovanovic

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Stefan Albert

    Institute for Mathematics, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  5. Lora Kovacheva

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Josef Shin

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  7. Richard Egger

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  8. Mahalakshmi Somayaji

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  9. Sevil Duvarci

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  10. Gaby Schneider

    Institute for Mathematics, Goethe University Frankfurt, Frankfurt, Germany
    Competing interests
    The authors declare that no competing interests exist.
  11. Jochen Roeper

    Institute for Neurophysiology, Goethe University Frankfurt, Frankfurt, Germany
    For correspondence
    roeper@em.uni-frankfurt.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2145-8742

Funding

National Institutes of Health (R01DA041705)

  • Jochen Roeper

Deutsche Forschungsgemeinschaft (CRC 1080)

  • Jochen Roeper

Gutenberg Forschungskolleg

  • Jochen Roeper

Deutsche Forschungsgemeinschaft (CRC 1193)

  • Jochen Roeper

Deutsche Forschungsgemeinschaft (DFG Priority Program 1665 (SCHN 1370/02-1))

  • Gaby Schneider

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All experiments and procedures involving mice were approved by the German Regierungspräsidium Darmstadt (V54-19c20/15-F40/28).

Reviewing Editor

  1. Olivier J Manzoni, Aix-Marseille University, INSERM, INMED, France

Publication history

  1. Received: May 13, 2019
  2. Accepted: October 2, 2019
  3. Accepted Manuscript published: October 3, 2019 (version 1)
  4. Version of Record published: October 14, 2019 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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Further reading

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    Background: The heterogeneity of white matter damage and symptoms in concussion has been identified as a major obstacle to therapeutic innovation. In contrast, most diffusion MRI (dMRI) studies on concussion have traditionally relied on group-comparison approaches that average out heterogeneity. To leverage, rather than average out, concussion heterogeneity, we combined dMRI and multivariate statistics to characterize multi-tract multi-symptom relationships.

    Methods: Using cross-sectional data from 306 previously-concussed children aged 9-10 from the Adolescent Brain Cognitive Development Study, we built connectomes weighted by classical and emerging diffusion measures. These measures were combined into two informative indices, the first representing microstructural complexity, the second representing axonal density. We deployed pattern-learning algorithms to jointly decompose these connectivity features and 19 symptom measures.

    Results: Early multi-tract multi-symptom pairs explained the most covariance and represented broad symptom categories, such as a general problems pair, or a pair representing all cognitive symptoms, and implicated more distributed networks of white matter tracts. Further pairs represented more specific symptom combinations, such as a pair representing attention problems exclusively, and were associated with more localized white matter abnormalities. Symptom representation was not systematically related to tract representation across pairs. Sleep problems were implicated across most pairs, but were related to different connections across these pairs. Expression of multi-tract features was not driven by sociodemographic and injury-related variables, as well as by clinical subgroups defined by the presence of ADHD. Analyses performed on a replication dataset showed consistent results.

    Conclusions: Using a double-multivariate approach, we identified clinically-informative, cross-demographic multi-tract multi-symptom relationships. These results suggest that rather than clear one-to-one symptom-connectivity disturbances, concussions may be characterized by subtypes of symptom/connectivity relationships. The symptom/connectivity relationships identified in multi-tract multi-symptom pairs were not apparent in single-tract/single-symptom analyses. Future studies aiming to better understand connectivity/symptom relationships should take into account multi-tract multi-symptom heterogeneity.

    Funding: financial support for this work from a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (GIG), an Ontario Graduate Scholarship (SS), a Restracomp Research Fellowship provided by the Hospital for Sick Children (SS), an Institutional Research Chair in Neuroinformatics (MD), as well as a Natural Sciences and Engineering Research Council CREATE grant (MD).

    1. Neuroscience
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    Striatal spiny projection neurons (SPNs) transform convergent excitatory corticostriatal inputs into an inhibitory signal that shapes basal ganglia output. This process is fine-tuned by striatal GABAergic interneurons (GINs), which receive overlapping cortical inputs and mediate rapid corticostriatal feedforward inhibition of SPNs. Adding another level of control, cholinergic interneurons (CINs), which are also vigorously activated by corticostriatal excitation, can disynaptically inhibit SPNs by activating α4β2 nicotinic acetylcholine receptors (nAChRs) on various GINs. Measurements of this disynaptic inhibitory pathway, however, indicate that it is too slow to compete with direct GIN-mediated feed-forward inhibition. Moreover, functional nAChRs are also present on populations of GINs that respond only weakly to phasic activation of CINs, such as parvalbumin-positive fast-spiking interneurons (PV-FSIs), making the overall role of nAChRs in shaping striatal synaptic integration unclear. Using acute striatal slices from mice we show that upon synchronous optogenetic activation of corticostriatal projections blockade of α4β2 nAChRs shortened SPN spike latencies and increased postsynaptic depolarizations. The nAChR-dependent inhibition was mediated by downstream GABA release, and data suggest that the GABA source was not limited to GINs that respond strongly to phasic CIN activation. In particular, the observed decrease in spike latency caused by nAChR blockade was associated with a diminished frequency of spontaneous inhibitory postsynaptic currents in SPNs, a parallel hyperpolarization of PV-FSIs, and was occluded by pharmacologically preventing cortical activation of PV-FSIs. Taken together, we describe a role for tonic (as opposed to phasic) activation of nAChRs in striatal function. We conclude that tonic activation of nAChRs by CINs maintains a GABAergic brake on cortically-driven striatal output by 'priming' feedforward inhibition, a process that may shape SPN spike timing, striatal processing and synaptic plasticity.