An arbitrary-spectrum spatial visual stimulator for vision research
- University of Tübingen, Germany
- University of Sussex, United Kingdom
Abstract
Visual neuroscientists require accurate control of visual stimulation. However, few stimulator solutions simultaneously offer high spatio-temporal resolution and free control over the spectra of the light sources, because they rely on off-the-shelf technology developed for human trichromatic vision. Importantly, consumer displays fail to drive UV-shifted short wavelength-sensitive photoreceptors, which strongly contribute to visual behaviour in many animals, including mice, zebrafish and fruit flies. Moreover, many non-mammalian species feature more than three spectral photoreceptor types. Here, we present a flexible, spatial visual stimulator with up to 6 arbitrary spectrum chromatic channels. It combines a standard digital light processing engine with open source hard- and software that can be easily adapted to the experimentalist's needs. We demonstrate the capability of this general visual stimulator experimentally in the in vitro mouse retinal whole-mount and the in vivo zebrafish. With this work, we intend to start a community effort of sharing and developing a common stimulator design for vision research.
Data availability
Part lists are provided in Tables 1-3 and Suppl. Table S1. Software scripts for stimulus calibration as well as design files for circuit boards and 3D-printed parts are provided at https://github.com/eulerlab/open-visual-stimulator. The visual stimulation software is provided at https://github.com/eulerlab/QDSpy.
Article and author information
Author details
Funding
Bundesministerium für Bildung und Forschung (FKZ: 01GQ1002)
- Katrin Franke
Max-Planck-Gesellschaft (M.FE.A.KYBE0004)
- Katrin Franke
European Commission (ERC-StG 'NeuroVisEco' 677687)
- Tom Baden
Horizon 2020 Framework Programme (Marie Skłodowska-Curie grant agreement No 674901)
- Tom Baden
- Thomas Euler
Biotechnology and Biological Sciences Research Council (BB/R014817/1)
- Tom Baden
Leverhulme Trust (PLP-2017-005)
- Tom Baden
Lister Institute of Preventive Medicine
- Tom Baden
Deutsche Forschungsgemeinschaft (Projektnummer 276693517 - SFB 1233)
- Thomas Euler
Medical Research Council (MC_PC_15071)
- Tom Baden
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 animal procedures adhered to the laws governing animal experimentation issued by the GermanGovernment (mouse) or all procedures were performed in accordance with the UK Animals (ScientificProcedures) act 1986 and approved by the animal welfare committee of the University of Sussex(zebrafish larvae).
Copyright
© 2019, Franke 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
-
- 4,842
- views
-
- 595
- downloads
-
- 72
- 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)
An arbitrary-spectrum spatial visual stimulator for vision research
eLife 8:e48779.
https://doi.org/10.7554/eLife.48779
Further reading
-
- Neuroscience
The neocortex comprises anatomically discrete yet interconnected areas that are symmetrically located across the two hemispheres. Determining the logic of these macrocircuits is necessary for understanding high level brain function. Here in mice, we have mapped the areal and laminar organization of the ipsi- and contralateral cortical projection onto the primary visual, somatosensory, and motor cortices. We find that although the ipsilateral hemisphere is the primary source of cortical input, there is substantial contralateral symmetry regarding the relative contribution and areal identity of input. Laminar analysis of these input areas show that excitatory Layer 6 corticocortical cells (L6 CCs) are a major projection pathway within and between the two hemispheres. Analysis of the relative contribution of inputs from supra- (feedforward) and infragranular (feedback) layers reveals that contra-hemispheric projections reflect a dominant feedback organization compared to their ipsi-cortical counterpart. The magnitude of the interhemispheric difference in hierarchy was largest for sensory and motor projection areas compared to frontal, medial, or lateral brain areas due to a proportional increase in input from L6 neurons. L6 CCs therefore not only mediate long-range cortical communication but also reflect its inherent feedback organization.
-
- Neuroscience
Reward-rate maximization is a prominent normative principle in behavioral ecology, neuroscience, economics, and AI. Here, we identify, compare, and analyze equations to maximize reward rate when assessing whether to initiate a pursuit. In deriving expressions for the value of a pursuit, we show that time’s cost consists of both apportionment and opportunity cost. Reformulating value as a discounting function, we show precisely how a reward-rate-optimal agent’s discounting function (1) combines hyperbolic and linear components reflecting apportionment and opportunity costs, and (2) is dependent not only on the considered pursuit’s properties but also on time spent and rewards obtained outside the pursuit. This analysis reveals how purported signs of suboptimal behavior (hyperbolic discounting, and the Delay, Magnitude, and Sign effects) are in fact consistent with reward-rate maximization. To better account for observed decision-making errors in humans and animals, we then analyze the impact of misestimating reward-rate-maximizing parameters and find that suboptimal decisions likely stem from errors in assessing time’s apportionment—specifically, underweighting time spent outside versus inside a pursuit—which we term the ‘Malapportionment Hypothesis’. This understanding of the true pattern of temporal decision-making errors is essential to deducing the learning algorithms and representational architectures actually used by humans and animals.
