+44 1634 720707 scientists@crsltd.com

Metropsis Research 2.0

Metropsis is a complete suite developed to assess visual function using non‑invasive psychophysical techniques. The system includes a wide variety of computerised vision tests which can accurately measure spatial  and colour discrimination in a wide population, including children and the elderly. Metropsis has been designed for routine use by non-experts; it is suitable for clinical trials and  natural history studies carried out at different sites.

Standard Configuration

 

Metropsis Research standard configuration includes the following hardware:

  • 32” 4K/UHD LCD Display++ monitor (to present the calibrated visual stimuli)
  • 21” Touchscreen (examiner’s monitor)
  • Five-button response box (used to obtain participant’s feedback)
  • Motorised table

Metropsis Research standard configuration includes a standard battery of vision tests:

  • Visual acuity (with Landolt C-ring)
  • Three colour vision tests: Cambridge Colour Test, low-vision version of the Cambridge Colour Test, Universal Colour Discrimination Test
  • Spatial Contrast Sensitivity Test (foveal, at photopic, mesopic and scotopic levels)

Options

 

Additional options include:

  • Luminare glare source
  • LiveTrack Lightning eye tracker
  • EyeLock chinrest

Optional vision tests require optional hardware. They consist of:

  • Peripheral Spatial Contrast Sensitivity Test (requires LiveTrack Lightning eye tracker and EyeLock chinrest)
  • Spatial Contrast Sensitivity Test under glare conditions (requires Luminare glare source)
  • Visual acuity under glare conditions (requires Luminare glare source)

Precision Display++ UHD technology

One of the key elements of Metropsis Research 2.0 is the calibrated 32” QLED LCD Display++ UHD Monitor, designed and manufactured exclusively by Cambridge Research Systems  (see some earlier Display++ references below). Display++ UHD makes it easy to display calibrated visual stimuli with precision timing and provides excellent control of colour and contrast.

Reliable stimulus presentation

Off-the-shelf LCD panels suffer from large colour and luminance fluctuations. This may be acceptable for screening tests, but general purpose LCD displays are unsuitable for precision testing. Novel hardware corrections developed by our Staff Scientists ensure that Display++ UHD reliably presents calibrated test patterns on every trial.

 

Highly accurate colour reproduction and spatial uniformity

 

Display++ UHD reproduces colours with high accuracy (average CIE DE2000 < 0.3) and high spatial uniformity (over 95%) across the screen area. It offers 10-bit RGB native colour precision, up to 12-bit with Deep Colour Technology, allowing the investigator to obtain very fine contrast levels.

 

Self-calibrating monitor

 

Display++ UHD is calibrated at the factory and maintains its calibrated light output thanks to a built-in light sensor. The sensor is isolated by the ambient light, so changes in the ambient light will not affect the calibration of the monitor.

Display++ UHD Technical Data

  • High quality 32” 4K UHD 3480×2160 IPS LCD panel with wide colour gamut Quantum Dot LED backlight

  • 10-bit RGB native colour precision, up to 12-bit with Deep Colour technology

  • Contrast ratio 1000:1

  • Grey-to-grey response time 4ms

  • 120Hz & 144Hz panel drive at 3480×2160 and 1920×1080

  • Real time calibration ensures accurate luminance, regardless of the effects of warm up and ageing

  • Hardware spatial uniformity correction, gamma correction, and CIE XYZ colour management system ensures accurate colour reproduction

  • Configurable wide dynamic range backlight, suitable for testing in photopic, mesopic and scotopic conditions; no filters required

  • Multiple synchronous TTL trigger outputs

  • Integrates with CRS audio, eye tracking and behavioural response devices, and compatible with solutions from other vendors

References

Hughes, A. E., Greenwood, J. A., Finlayson, N. J., & Schwarzkopf, D. S. (2019). Population receptive field estimates for motion-defined stimuli. NeuroImage.

Kohl, C., Spieser, L., Forster, B., Bestmann, S., & Yarrow, K. (2019). The neurodynamic decision variable in human multi-alternative perceptual choice. Journal of cognitive neuroscience, 31(2), 262-277.

Ghodrati, M., Zavitz, E., Rosa, M. G., & Price, N. S. (2019). Contrast and luminance adaptation alter neuronal coding and perception of stimulus orientation. Nature communications, 10(1), 941.

DiMattina, C., & Baker, C. L. (2019). Modeling second-order boundary perception: A machine learning approach. PLoS computational biology, 15(3), e1006829.

Flynn, O. J., & Jeffrey, B. G. (2019). Scotopic contour and shape discrimination using radial frequency patterns. Journal of vision, 19(2), 7-7. Slattery, T. J., & Vasilev, M. R. (2019). An eye-movement exploration into return-sweep targeting during reading. Attention, Perception, & Psychophysics, 1-7.

Zhang, Q., & Li, S. (2019). The roles of spatial frequency in category‐level visual search of real‐world scenes. PsyCh journal. Smith, P. L., & Corbett, E. A. (2019). Speeded multielement decision-making as diffusion in a hypersphere: Theory and application to double-target detection. Psychonomic bulletin & review, 26(1), 127-162.

Takao, S., Clifford, C. W., & Watanabe, K. (2019). Ebbinghaus illusion depends more on the retinal than perceived size of surrounding stimuli. Vision research, 154, 80-84.

Wright, D., & Chouinard, P. A. (2019). Effects of multitasking and intention–behaviour consistency when facing yellow traffic light uncertainty. Attention, Perception, & Psychophysics, 1-18.

Beatty, P. J., Buzzell, G. A., Roberts, D. M., & McDonald, C. G. (2018). Speeded response errors and the error-related negativity modulate early sensory processing. Neuroimage, 183, 112-120.

Kumaran, N., Ripamonti, C., Kalitzeos, A., Rubin, G. S., Bainbridge, J. W., & Michaelides, M. (2018). Severe Loss of Tritan Color Discrimination in RPE65 Associated Leber Congenital Amaurosis. Investigative ophthalmology & visual science, 59(1), 85-93.

Kawai, K., Chandler, D. M., & Ohashi, G. (2018, September). On the Role of Shaped-Noise Visibility for Post-Compression Image Enhancement. In International Conference on Global Research and Education (pp. 195-203). Springer, Cham.

Tamura, H., Higashi, H., & Nakauchi, S. (2018). Dynamic Visual Cues for Differentiating Mirror and Glass. Scientific reports, 8(1), 8403. doi: 10.1038/s41598-018-26720-x

Goettker, A., Braun, D. I., Schütz, A. C., & Gegenfurtner, K. R. (2018). Execution of saccadic eye movements affects speed perception. Proceedings of the National Academy of Sciences, 201704799 doi.org/10.1073/pnas.1704799115

Balsdon T, Clifford CWG. 2018 Visual processing: conscious until proven otherwise. R. Soc. open sci. 5: 171783.

Park, A. S., Bedggood, P. A., Metha, A. B., & Anderson, A. J. (2017). Masking of random-walk motion by flicker, and its role in the allocation of motion in the on-line jitter illusion. Vision research, 137, 50-60. doi.org/10.1016/j.visres.2017.06.003

Palmer, C. J., & Clifford, C. W. (2017). Perceived Object Trajectory Is Influenced by Others’ Tracking Movements. Current Biology, 27(14), 2169-2176 doi.org/10.1016/j.cub.2017.06.019

Mannion, D. J., Donkin, C., & Whitford, T. J. (2017). No apparent influence of psychometrically-defined schizotypy on orientation-dependent contextual modulation of visual contrast detection. PeerJ, 5, e2921 doi.org/10.7717/peerj.2921

Braun, D. I., Schütz, A. C., & Gegenfurtner, K. R. (2017). Visual sensitivity for luminance and chromatic stimuli during the execution of smooth pursuit and saccadic eye movements. Vision research, 136, 57-69. doi.org/10.1016/j.visres.2017.05.008

Vercillo, T., Carrasco, C., & Jiang, F. (2017). Age-Related Changes in Sensorimotor Temporal Binding. Frontiers in Human Neuroscience, 11, 500 doi.org/10.3389/fnhum.2017.00500

Agaoglu, M. N., & Chung, S. T. (2017). Interaction between stimulus contrast and pre-saccadic crowding. Royal Society open science, 4(2), 160559. http://doi.org/10.1098/rsos.160559

Valsecchi, M. & Gegenfurtner, K.R. (2016). Dynamic re-calibration of perceived size in fovea and periphery through predictable size changes. Current Biology, 26, 59–63

Souto, D., Gegenfurtner, K.R. & Schütz, A.C. (2016). Saccade adaptation and visual uncertainty. Frontiers in Human Neuroscience, 10:227 Braun, D. I., & Gegenfurtner, K. R. (2016). Dynamics of oculomotor direction discrimination. Journal of Vision, 16(13):4, 1–26, doi.org/10.1167/16.13.4

DiMattina, C. (2016). Comparing models of contrast gain using psychophysical experiments. Journal of Vision, 16(9):1, 1–18, doi.org/10.1167/16.9.1

Linxi Zhao, Caroline Sendek, Vandad Davoodnia, Reza Lashgari, Mitchell W. Dul, Qasim Zaidi, Jose-Manuel Alonso; Effect of Age and Glaucoma on the Detection of Darks and Lights. Invest. Ophthalmol. Vis. Sci. 2015;56(11):7000-7006. doi.org/10.1167/iovs.15-16753

Contact our Staff Scientist