Rethinking How the Brain Sees Visual Features
Brain scientists will have to rethink the current theory of how the visual processing region of the brain is organized to analyze basic information about the geometry of the environment, according to Duke neurobiologists. In a new study reported in the June 26, 2003, Nature, they studied the visual-processing region — called the visual cortex — of ferrets, as the animals’ brains responded to complex patterns.
The results, they said, indicated that clusters of neurons in that region do not specialize in recognizing a particular combination of stimulus features, as previously believed. Rather, individual clusters react to a broad range of stimulus combinations — combinations that can be predicted by understanding the fundamental spatial and temporal properties of the visual stimulus. The scientists’ research was supported by the National Eye Institute.
The visual cortex — a layer of brain tissue at the back of the head — is the first area within the cerebral cortex that processes neural signals from the eye. It performs the basic tasks of recognizing the geometric features of a scene before relaying that information to higher brain regions, where such basic visual data are transformed into the conscious perception of the visual world.
Current theory of visual cortex organization holds that in mammals, including humans, the visual cortex consists of overlapping “feature maps.” Each map is an orderly arrangement of neuronal clusters that represents a particular stimulus feature, such as the orientation of edges, their direction of motion, or their spacing. Before these new experiments were performed, it was thought that the response properties of neurons could be predicted by their location relative to the places in the visual cortex where different feature maps overlap. In this view, clusters of neurons are “specialists” for the detection of certain combinations of visual features, such as a set of parallel lines of a certain orientation, spaced a certain distance apart and moving at a specific speed.
In their experiments, Duke neurobiologists — graduate student Amit Basole, Assistant Professor Leonard White and Professor David Fitzpatrick — decided to go beyond previous studies in which animals were exposed only to simple visual stimuli consisting of parallel bars, or gratings, with different spacings and moving at different speeds at a right angle to the bars.
“Studies with gratings can tell you a lot,” said Fitzpatrick. “For example, you can get a sense of maps of orientation if you change the orientation of the grating. And you can also get information about how properties like spatial frequency are mapped by changing the distance between the bars in the grating, and mapping how that changes patterns of neural activity.
“The underlying assumption was that, in a sense there was a ‘place code’ for stimulus combinations,” said Fitzpatrick. “So, a particular orientation, spatial frequency or direction would activate a certain cluster of neurons in the cortex; and changing the orientation, direction or spatial frequency would shift the locus of activity in a predictable way — one that signified which attribute had been changed.”
However, said Fitzpatrick, “these stimuli are really limiting because you can only look at certain stimulus combinations.” To explore how the visual cortex reacted to more complex combinations of stimuli, the researchers exposed ferrets to patterns consisting of short line segments whose orientation, length, direction and speed of motion could be varied independently.
Said White, “With these texture patterns, we have the ability to let different properties interact with one another in ways that are closer to the kinds of stimulus interactions that are often present in the visual environment.” A striking example of such interactions is the so-called barber pole illusion, he said.
“While the barber pole is moving horizontally as the pole spins about its axis, it creates a perception that the lines are moving up,” said White. “The perception induced by the interaction between the orientation of the lines and the direction of motion is the sort of phenomenon that Amit was seeking to understand in terms of neural responses.”
The researchers used a technique called optical imaging to detect brain activity in the animals’ visual cortex by shining light of wavelengths that specifically revealed increased blood flow to more active areas. Also, to confirm that the images portrayed actual increases in brain activity, the researchers also recorded electrical activity of individual neurons in different cortical regions during exposure to the patterns.
The effects of changing the visual stimuli on the activity patterns in the animals’ brains were surprising, said Fitzpatrick.
“From the prevailing view, if you kept the orientation of the bars constant and varied the other parameters, you might not expect to see much of a change in the maps of activity,” said Fitzpatrick. But, in fact, we saw shifts in activity that were much greater than we expected, and the patterns looked identical to those that were produced by textures that had different combinations of line orientation, direction, length and speed.
“So, this makes clear that thinking about maps in the cortex as consisting of clusters devoted to particular combinations of features is too simplistic when you’re dealing with stimuli that are much more like those you encounter in the visual world,” he said.
“What we’re seeing is that a given spot in the cortex seems to be integrating a number of different stimulus components. All of these components figure into what determines the activation of a given spot in the map.”
In this new way of thinking about the visual cortex, it is still possible to consider the clusters of neurons as specialists; neurons in these new studies responded to complex visual patterns with remarkable selectivity, said Fitzpatrick. However, these findings show that what these clusters specialize in is not the recognition of a unique combination of stimulus features, but the detection of a narrow band of spatial and temporal information that may be produced by a surprising large combination of stimulus features.
The researchers plan further studies to attempt to understand how the visual cortex is organized — for example, seeking to obtain faster snapshots of brain activity, to obtain more detail in changes in brain activity. They are also working with other colleagues to create mathematical models that might reveal the strategy by which the brain has organized its visual perceptual circuitry.
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