Time to think about visual neuroscience

by Poppy Sharp, PhD candidate at the Center for Mind/Brain Sciences, University of Trento.

All is not as it seems

We all delight in discovering that what we see isn’t always the truth. Think optical illusions: as a kid I loved finding the hidden images in Magic Eye stereogram pictures. Maybe you remember a surprising moment when you realised you can’t always trust your eyes. Here’s a quick example. In the image below, cover your left eye and stare at the cross, then slowly move closer towards the screen. At some point, instead of seeing what’s really there, you’ll see a continuous black line. This happens when the WAB logo falls in a small patch on the retinae of your eyes where the nerve fibres leave in a bundle, and consequently this patch has no light receptors – a blind spot. When the logo is in your blind spot, your visual system fills in the gap using the available information. Since there are lines on either side, the assumption is made that the line continues through the blind spot.

Illusions reveal that our perception of the world results from the brain building our visual experiences, using best guesses as to what’s really out there. Most of the time you don’t notice, because the visual system has been adapted over years of evolution and then been honed by your lifetime of perceptual experiences, and is pretty good at what it does.

WAB vision

For vision scientists, illusions can provide clues about the way the visual system builds our experiences. We refer to our visual experience of something as a ‘percept’, and use the term ‘stimulus’ for the thing which prompted that percept. The stimulus could be something as simple as a flash of light, or more complex like a human face. Vision science is all about carefully designing experiments so we can tease apart the relationship between the physical stimulus out in the world and our percept of it. In this way, we learn about the ongoing processes in the brain which allow us to do everything from recognising objects and people, to judging the trajectory of a moving ball so we can catch it.

We can get insight into what people perceived by measuring their behavioural responses. Take a simple experiment: we show people an arrow to indicate whether to pay attention to the left or the right side of the screen, then they see either one or two flashes of light flash quickly on one side, and have to press a button to indicate how many flashes they saw. There are several behavioural measures we could record here. Did the cue help them be more accurate at telling the difference between one or two flashes? Did the cue allow them to respond more quickly? Were they more confident in their response? These are all behavioural measures. In addition, we can also look at another type of measure: their brain activity. Recording brain activity allows unique insights into how our experiences of the world are put together, and investigation of exciting new questions about the mind and brain.

Rhythms of the brain

Your brain is a complex network of cells using electrochemical signals to communicate with one another. We can take a peek at your brain waves by measuring the magnetic fields associated with the electrical activity of your brain. These magnetic fields are very small, so to record them we need a machine called an MEG scanner (magnetoencephalography) which has many extremely sensitive sensors called SQUIDs (superconducting quantum interference devices). The scanner somewhat resembles a dryer for ladies getting their blue rinse done, but differs in that it’s filled with liquid helium and costs about three million euros.

A single cell firing off an electrical signal would have too small a magnetic field to be detected, but since cells tend to fire together as groups, we can measure these patterns of activity in the MEG signal. Then we look for differences in the patterns of activity under different experimental conditions, in order to reveal what’s going on in the brain during different cognitive processes. For example, in our simple experiment from before with a cue and flashes of light, we would likely find differences in brain activity when these flashes occur at an expected location as compared to an unexpected one.

One particularly fascinating way we can characterise patterns of brain activity is in terms of the the rhythms of the brain. Brain activity is an ongoing symphony of multiple groups of cells firing in concert. Some groups fire together more often (i.e. at high frequency), whereas others may also be firing together in a synchronised way, but firing less often (low frequency). These different patterns of brain waves generated by cells forming different groups and firing at various frequencies are vital for many important processes, including visual perception.

What I’m working on

For as many hours of the day as your eyes are open, a flood of visual information is continuously streaming into your brain. I’m interested in how the visual system makes sense of all that information, and prioritises some things over others. Like many researchers, the approach we use is to show simple stimuli in a controlled setting, in order to ask questions about fundamental low level visual processes. We then hope that our insights generalise to more natural processing in the busy and changeable visual environment of the ‘real world’. My focus is on temporal processing. Temporal processing can refer to a lot of things, but as far as my projects go we mean how you deal with stimuli occurring very close together in time (tens of milliseconds apart). I’m investigating how this is influenced by expectations, so in my experiments we manipulate expectations about where in space stimuli will be, and also your expectations about when they will appear. This is achieved using simple visual cues to direct your attention to, for example, a certain area of the screen.

When stimuli rapidly follow one another in time, sometimes it’s important to be parse them into separate percepts whereas other times it’s more appropriate to integrate them together. There’s always a tradeoff between the precision and stability of the percepts built by the visual system.  The right balance between splitting up stimuli into separate percepts as opposed to blending them into a combined percept depends on the situation and what you’re trying to achieve at that moment.

Let’s illustrate some aspects of this idea about parsing versus integrating stimuli with a story, out in the woods at night. If some flashes of light come in quick succession from the undergrowth, this could be the moonlight reflecting off the eyes of a moving predator. In this case, your visual system needs to integrate these stimuli into a percept of the predator moving through space. But a similar set of several stimuli flashing up from the darkness could also be multiple predators next to each other, in which case it’s vital that you parse the incoming information and perceive them separately. Current circumstances and goals determine the mode of temporal processing that is most appropriate.

I’m investigating how expectations about where stimuli will be can influence your ability to either parse them into separate percepts or to form an integrated percept. Through characterising how expectations influence these two fundamental but opposing temporal processes, we hope to gain insights not only into the processes themselves, but also into the mechanisms of expectation in the visual system. By combining behavioural measures with measures of brain activity (collected using the MEG scanner), we are working towards new accounts of the dynamics of temporal processing and factors which influence it. In this way, we better our understanding of the visual system’s impressive capabilities in building our vital visual experiences from the lively stream of information entering our eyes.

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