1. Neuroscience
Download icon

Striatal dynamics explain duration judgments

  1. Thiago S Gouvêa
  2. Tiago Monteiro
  3. Asma Motiwala
  4. Sofia Soares
  5. Christian Machens
  6. Joseph J Paton  Is a corresponding author
  1. Champalimaud Centre for the Unknown, Portugal
Research Article
  • Cited 71
  • Views 5,837
  • Annotations
Cite this article as: eLife 2015;4:e11386 doi: 10.7554/eLife.11386

Abstract

The striatum is an input structure of the basal ganglia implicated in several time-dependent functions including reinforcement learning, decision making, and interval timing. To determine whether striatal ensembles drive subjects' judgments of duration, we manipulated and recorded from striatal neurons in rats performing a duration categorization psychophysical task. We found that the dynamics of striatal neurons predicted duration judgments, and that simultaneously recorded ensembles could judge duration as well as the animal. Furthermore, striatal neurons were necessary for duration judgments, as muscimol infusions produced a specific impairment in animals' duration sensitivity. Lastly, we show that time as encoded by striatal populations ran faster or slower when rats judged a duration as longer or shorter, respectively. These results demonstrate that the speed with which striatal population state changes supports the fundamental ability of animals to judge the passage of time.

Article and author information

Author details

  1. Thiago S Gouvêa

    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
    Competing interests
    The authors declare that no competing interests exist.

  2. Tiago Monteiro

    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
    Competing interests
    The authors declare that no competing interests exist.

  3. Asma Motiwala

    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
    Competing interests
    The authors declare that no competing interests exist.

  4. Sofia Soares

    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
    Competing interests
    The authors declare that no competing interests exist.

  5. Christian Machens

    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
    Competing interests
    The authors declare that no competing interests exist.

  6. Joseph J Paton

    Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
    For correspondence
    joe.paton@neuro.fchampalimaud.org
    Competing interests
    The authors declare that no competing interests exist.

Ethics

Animal experimentation: All experiments were in accordance with the European Union Directive 86/609/EEC and approved by the Portuguese Veterinary General Board (Direcção-Geral de Veterinária, project approval 014303 - 0420/000/000/2011)

Reviewing Editor

  1. Timothy Behrens, Oxford University, United Kingdom

Publication history

  1. Received: September 3, 2015
  2. Accepted: December 7, 2015
  3. Accepted Manuscript published: December 7, 2015 (version 1)
  4. Version of Record published: January 12, 2016 (version 2)

Copyright

© 2015, Gouvêa et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 5,837
    Page views
  • 1,206
    Downloads
  • 71
    Citations

Article citation count generated by polling the highest count across the following sources: Scopus, Crossref, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Categories and tags

Research organism

    1. Of interest

    Structure and function of axo-axonic inhibition

    Casey M Schneider-Mizell et al.
  2. Further reading

Further reading

    1. Neuroscience

    Structure and function of axo-axonic inhibition

    Casey M Schneider-Mizell et al.
    Research Article Updated

    Inhibitory neurons in mammalian cortex exhibit diverse physiological, morphological, molecular, and connectivity signatures. While considerable work has measured the average connectivity of several interneuron classes, there remains a fundamental lack of understanding of the connectivity distribution of distinct inhibitory cell types with synaptic resolution, how it relates to properties of target cells, and how it affects function. Here, we used large-scale electron microscopy and functional imaging to address these questions for chandelier cells in layer 2/3 of the mouse visual cortex. With dense reconstructions from electron microscopy, we mapped the complete chandelier input onto 153 pyramidal neurons. We found that synapse number is highly variable across the population and is correlated with several structural features of the target neuron. This variability in the number of axo-axonic ChC synapses is higher than the variability seen in perisomatic inhibition. Biophysical simulations show that the observed pattern of axo-axonic inhibition is particularly effective in controlling excitatory output when excitation and inhibition are co-active. Finally, we measured chandelier cell activity in awake animals using a cell-type-specific calcium imaging approach and saw highly correlated activity across chandelier cells. In the same experiments, in vivo chandelier population activity correlated with pupil dilation, a proxy for arousal. Together, these results suggest that chandelier cells provide a circuit-wide signal whose strength is adjusted relative to the properties of target neurons.

    1. Neuroscience

    Dopamine enhances model-free credit assignment through boosting of retrospective model-based inference

    Lorenz Deserno et al.
    Research Article Updated

    Dopamine is implicated in representing model-free (MF) reward prediction errors a as well as influencing model-based (MB) credit assignment and choice. Putative cooperative interactions between MB and MF systems include a guidance of MF credit assignment by MB inference. Here, we used a double-blind, placebo-controlled, within-subjects design to test an hypothesis that enhancing dopamine levels boosts the guidance of MF credit assignment by MB inference. In line with this, we found that levodopa enhanced guidance of MF credit assignment by MB inference, without impacting MF and MB influences directly. This drug effect correlated negatively with a dopamine-dependent change in purely MB credit assignment, possibly reflecting a trade-off between these two MB components of behavioural control. Our findings of a dopamine boost in MB inference guidance of MF learning highlight a novel DA influence on MB-MF cooperative interactions.

    1. Developmental Biology
    2. Neuroscience

    insomniac links the development and function of a sleep-regulatory circuit

    Qiuling Li et al.
    Research Article Updated

    Although many genes are known to influence sleep, when and how they impact sleep-regulatory circuits remain ill-defined. Here, we show that insomniac (inc), a conserved adaptor for the autism-associated Cul3 ubiquitin ligase, acts in a restricted period of neuronal development to impact sleep in adult Drosophila. The loss of inc causes structural and functional alterations within the mushroom body (MB), a center for sensory integration, associative learning, and sleep regulation. In inc mutants, MB neurons are produced in excess, develop anatomical defects that impede circuit assembly, and are unable to promote sleep when activated in adulthood. Our findings link neurogenesis and postmitotic development of sleep-regulatory neurons to their adult function and suggest that developmental perturbations of circuits that couple sensory inputs and sleep may underlie sleep dysfunction in neurodevelopmental disorders.