The origin and properties of flicker-induced geometric phosphenes

A Model for the Origin and Properties of Flicker-Induced Geometric Phosphenes (PDF).

Many people see geometric patterns when looking at flickering lights. The patterns depend on the frequency, color, and intensity of the flickering. Different people report seeing similar shapes, which are called “form constants”. 

Flicker hallucinations are best induced using a Ganzfeld (German for “entire field”): an immersive, full-field, uniform visual stimulation. Frequencies ranging from 8 to 30 Hz are most effective. 

This effect is used by numerous sound-and-light machines sold for entertainment purposes. Some of these devices claim to alter the frequency of brain waves. There is no scientific evidence for this. However, the flickering stimulus may increase the amplitude of oscillations that are already present in the brain, to the point where geometric visual hallucinations can occur.

Figure 1. Illustrations of basic phosphene patterns (form constants) as they appear subjectively (left), and their transformation to planar waves in cortical coordinates (right).

How do flickering lights cause geometric visual hallucinations? Roughly, flickering lights confuse the eye and the brain, causing them to see geometric shapes that aren't there. The phenomenon is related to how bold patterns can create optical illusions, but in this case the pattern varies in time, rather than space.

Our hypothesis is that the flickering interacts with natural ongoing oscillations in visual cortex, exciting a specific frequency of brain waves. This increases the activity in visual cortex. This increase in excitability is similar to what occurs on some hallucinogens. 

The simpler patterns, like ripples and spots, are mathematically related to the Turing patterns in animal coat patterns. More complex patterns occur when these instabilities interact with the brain's pattern recognition circuits. For more information, including the mathematical details of the model, head over and check out the paper.

The theory predicts that low frequencies (8-12 Hz) are more likely to induce spot-like patterns, and that high frequencies (12-30 Hz) are more likely to induce striped or ripple patterns. Anecdotally, I have tested this on myself and find it to be approximately correct for a white flicker Ganzfeld stimulus. I also find that low-frequency red-green flicker reliably induces checkerboard patterns, and that red-blue flicker reliably induces an almost quasicrystaline pattern of triangles and hexagons.

Many thanks to Matt Stoffregen and Bard Ermentrout for making this possible, as well as the CNBC undergraduate training program. The paper can be cited as

Rule, M., Stoffregen, M. and Ermentrout, B., 2011. A model for the origin and properties of flicker-induced geometric phosphenes. PLoS Comput Biol, 7(9), p.e1002158.

 

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Extras that didn't make it into the final paper:

Below is a variant of Figure 6 inspired by Robert Munafo's visualization of the parameter space of the Gray-Scott reaction-diffusion model. It shows how the evoked patterns vary depending on the flicker frequency (horizontal axis) and amplitude (vertical axis). Activity levels of excitatory and inhibitory cells are colored in yellow and blue, respectively.

It's computed by integrating the periodically-driven 2D Wilson-Cowan on the GPU. We drive the system with a uniform periodic stimulus, but vary the integration time step $\Delta t$ so that each location perceives a different frequency. The continuous simulation causes patterns to "spill over" into the nearby areas (where patterns are not spontaneously stable), so we didn't include this version in the paper.

Primary visual cortex isn't a perfectly square, periodic domain, and we also simulated patches resembling the shape of this brain area. Here, it was important to create a soft absorbing boundary, otherwise the sharp boundary itself promotes pattern formation. Horizontal and vertical stripes are stable, and this may account for why radial and tunnel-like patterns are slightly more common.

Videos of simulation:

Here is a video of the striped patterns emerging on a rectangular domain

 

 

And the hexagonal patterns:

 

Here is the stripe pattern again, transformed into perceptual coordinates:

 

Emerging patterns are associated with a "critical wavenumber", which sets the spatial scale of the instabilities in the model.  If you visualize the amplitude of the Fourier coefficients of the 2D system as patterns emerge, you see that isolated peaks in spatial frequency appear (along with their harmonics). The example below is for a striped pattern: