An NMDA receptor-dependent mechanism for subcellular segregation of sensory inputs in the tadpole optic tectum

  1. Ali S Hamodi
  2. Zhenyu Liu
  3. Kara G Pratt  Is a corresponding author
  1. University of Wyoming, United States
  2. University of Wyomin, United States

Abstract

In the vertebrate CNS, afferent sensory inputs are targeted to specific depths or layers of their target neuropil. This patterning exists ab initio, from the very beginning, and therefore has been considered an activity-independent process. However, here we report that, during circuit development, the subcellular segregation of the visual and mechanosensory inputs to specific regions of tectal neuron dendrites in the tadpole optic tectum requires NMDA receptor activity. Blocking NMDARs during the formation of these sensory circuits, or removing the visual set of inputs, leads to less defined segregation, and suggests a correlation-based mechanism in which correlated inputs wire to common regions of dendrites. This can account for how two sets of inputs form synapses onto different regions of the same dendrite. Blocking NMDA receptors during later stages of circuit development did not disrupt segregation, indicating a critical period for activity-dependent shaping of patterns of innervation.

Article and author information

Author details

  1. Ali S Hamodi

    Department of Zoology and Physiology, University of Wyoming, Laramie, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Zhenyu Liu

    Department of Zoology and Physiology, University of Wyomin, Laramie, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Kara G Pratt

    Department of Zoology and Physiology, University of Wyoming, Laramie, United States
    For correspondence
    Kpratt4@uwyo.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6743-4757

Funding

Office of Experimental Program to Stimulate Competitive Research ((Outside the Box) Grant number 4201-11951-1001498 G)

  • Zhenyu Liu
  • Kara G Pratt

National Institute of General Medical Sciences (P30-GM-32128)

  • Ali S Hamodi
  • Zhenyu Liu
  • Kara G Pratt

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 experimental protocols have been approved by the University of Wyoming's Institutional Animal Care and Use Committee (IACUC). The protocol (# 20140411KP00089-03) was approved 04/11/16 to 04/10/17.

Copyright

© 2016, Hamodi 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

  • 915
    views
  • 198
    downloads
  • 9
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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)

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

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

  1. Ali S Hamodi
  2. Zhenyu Liu
  3. Kara G Pratt
(2016)
An NMDA receptor-dependent mechanism for subcellular segregation of sensory inputs in the tadpole optic tectum
eLife 5:e20502.
https://doi.org/10.7554/eLife.20502

Share this article

https://doi.org/10.7554/eLife.20502

Further reading

    1. Neuroscience
    Mohsen Alavash
    Insight

    Combining electrophysiological, anatomical and functional brain maps reveals networks of beta neural activity that align with dopamine uptake.

    1. Neuroscience
    Nicolas Langer, Maurice Weber ... Ce Zhang
    Tools and Resources

    Memory deficits are a hallmark of many different neurological and psychiatric conditions. The Rey–Osterrieth complex figure (ROCF) is the state-of-the-art assessment tool for neuropsychologists across the globe to assess the degree of non-verbal visual memory deterioration. To obtain a score, a trained clinician inspects a patient’s ROCF drawing and quantifies deviations from the original figure. This manual procedure is time-consuming, slow and scores vary depending on the clinician’s experience, motivation, and tiredness. Here, we leverage novel deep learning architectures to automatize the rating of memory deficits. For this, we collected more than 20k hand-drawn ROCF drawings from patients with various neurological and psychiatric disorders as well as healthy participants. Unbiased ground truth ROCF scores were obtained from crowdsourced human intelligence. This dataset was used to train and evaluate a multihead convolutional neural network. The model performs highly unbiased as it yielded predictions very close to the ground truth and the error was similarly distributed around zero. The neural network outperforms both online raters and clinicians. The scoring system can reliably identify and accurately score individual figure elements in previously unseen ROCF drawings, which facilitates explainability of the AI-scoring system. To ensure generalizability and clinical utility, the model performance was successfully replicated in a large independent prospective validation study that was pre-registered prior to data collection. Our AI-powered scoring system provides healthcare institutions worldwide with a digital tool to assess objectively, reliably, and time-efficiently the performance in the ROCF test from hand-drawn images.