RPG: A low-cost, open-source, high-performance solution for displaying visual stimuli

BACKGROUND

The development of new high throughput approaches for neuroscience such as high-density silicon probes and 2-photon imaging have led to a renaissance in visual neuroscience. However, generating the stimuli needed to evoke activity in the visual system still represents a non-negligible difficulty for experimentalists. While several widely used software toolkits exist to deliver such stimuli, they all suffer from some shortcomings. Primarily, the hardware needed to effectively display such stimuli comes at a significant financial cost, and secondly, triggering and/or timing the stimuli such that it can be accurately synchronized with other devices requires the use of legacy hardware, further hardware, or bespoke solutions.

RESULTS

Here we present RPG (Raspberry Pi Gratings), a Python package written for the Raspberry Pi, which overcomes these issues. Specifically, the Raspberry Pi is a low-cost, credit card sized computer with general purpose input/output pins, allowing RPG to be triggered to deliver stimuli and to provide real-time feedback on stimulus timing. RPG delivers stimuli at 60 frames per second and the feedback of frame timings is accurate to 10s of microseconds.

COMPARISON WITH EXISTING METHOD(S)

With respect to the accuracy of frame timings, the performance of RPG is at least as accurate as commonly used packages. However, the inbuilt ability to trigger stimuli and the real-time feedback of frame timings will be extremely useful for certain experiments.

CONCLUSIONS

RPG provides a simple to use Python interface that is capable of generating drifting sine wave gratings, Gabor patches and displaying raw images/video.

Comparing biological and artificial vision systems: Network measures of functional connectivity

Advances in Deep Convolutional Neural Networks (DCNN) provide new opportunities for computational neuroscience to pose novel questions regarding the function of biological visual systems. Some attempts have been made to utilize advances in machine learning to answer neuroscientific questions, but how to appropriately make comparisons between the biological systems and artificial neural network structure is an open question. This analysis quantifies network properties of the mouse visual system and a common DCNN model (VGG16), to determine if this comparison is appropriate. Utilizing weighted graph-theoretic measures of node density (weighted node-degree), path length, local clustering coefficient, and betweenness, differences in functional connectivity patterns in the modern artificial computer vision system and the biological vision system are quantified. Results show that the mouse exhibits network measure distributions more similar to Poisson than normal, whereas the VGG16 exhibits network measure distributions with a more Gaussian shape than the sampled biological network. The artificial network shows higher density measures and shorter path lengths in comparison to the biological network. These results show that training a VGG16 for an object recognition task is unlikely to produce a network whose functional connectivity is similar to the mammalian visual system.

Peripheral resolution and contrast sensitivity: Effects of stimulus drift

Optimal temporal modulation of the stimulus can improve foveal contrast sensitivity. This study evaluates the characteristics of the peripheral spatiotemporal contrast sensitivity function in normal-sighted subjects. The purpose is to identify a temporal modulation that can potentially improve the remaining peripheral visual function in subjects with central visual field loss. High contrast resolution cut-off for grating stimuli with four temporal frequencies (0, 5, 10 and 15Hz drift) was first evaluated in the 10° nasal visual field. Resolution contrast sensitivity for all temporal frequencies was then measured at four spatial frequencies between 0.5 cycles per degree (cpd) and the measured stationary cut-off. All measurements were performed with eccentric optical correction. Similar to foveal vision, peripheral contrast sensitivity is highest for a combination of low spatial frequency and 5-10Hz drift. At higher spatial frequencies, there was a decrease in contrast sensitivity with 15Hz drift. Despite this decrease, the resolution cut-off did not vary largely between the different temporal frequencies tested. Additional measurements of contrast sensitivity at 0.5 cpd and resolution cut-off for stationary (0Hz) and 7.5Hz stimuli performed at 10, 15, 20 and 25° in the nasal visual field also showed the same characteristics across eccentricities.