Our visual perception of the world is often considered relatively stable. However, like all our cognitive functions, visual processing is shaped by our experiences. During both development and adulthood, learning can alter visual perception. For example, enhanced visual discrimination of similar patterns is a learned skill crucial for reading. In a new research study published in Current Biology, scientists have now discovered the neuronal changes that occur during learning to enhance discrimination against closely related visual images.
This study, led by first author Dr. Joseph Schumacher and senior author Dr. David Fitzpatrick of the Max Planck Florida Institute for Neuroscience, establishes a transformative approach to studying perceptual learning in the brain. Researchers imaged the activity of large numbers of individual neurons over days to track the changes that occur while learning a visual discrimination task, and conducted these experiments in a new animal model, the tree shrew.
The tree shrew is a small mammal with visual characteristics related to humans, including a high degree of visual acuity and a similarly orderly spatial arrangement of visually responsive neurons in the brain. As the researchers show, these animals can also learn complex behavioral tasks, making them ideal for understanding how experience shapes visual perception. In this study, tree shrews were trained to distinguish between very similar visual images: identical black lines that differed only by a small change in orientation (22.5 degrees). In the task, the presentation of the lines in one direction was rewarded with a drop of juice. Over the course of days, tree shrews learned to distinguish between the two similar visual images, licking only in response to the lines in the rewarded orientation and abstaining from licking the lines in the non-rewarded orientation.
The scientists combined this behavioral task with measurements of neural activity in V1, an area of the brain essential for visual processing. The neurons in this region are activated by specific features of visual input, such as the orientation of light-dark edges. Individual neurons show ‘preference’ for specific edge orientations, responding with the highest activity to these orientations and with progressively lower activity or no activity at edges oriented further from the preferred orientation. In this way, a visual scene with edges of different orientations activates certain subsets of neurons to generate a neural activity pattern that encodes the information necessary for visual perception.
Schumacher and colleagues found that learning visual discrimination in the tree shrew was associated with an improvement in the difference in the patterns of neural activity evoked by the two visual images. This was mainly due to an increase in the amount of neural activity in response to the presentation of the rewarded stimulus orientation relative to the non-rewarded orientation. But this was not just an overall increase in neuronal responses to the rewarded stimulus. When the scientists examined the changes more closely, they found that this was mediated by changes in the activity of a remarkably specific subset of neurons: those whose orientation preference was optimal for distinguishing the orientation of the rewarded stimulus from the non-rewarded stimulus.
To fully understand the effect of learning on visual perception, the authors next examined whether the changes in neuronal activity that enhanced visual discrimination persisted outside the learned task context. Interestingly, they found that the neuronal changes not only persisted, but were accompanied by changes in the trained tree shrew’s ability to perform other discriminations. This included improvements for some stimulus orientations as well as limitations for others — behavioral changes that were exactly what would be expected given the changes in the responses of this particular subset of neurons.
“This work demonstrates specific experience-driven changes in neuron activity that affect perception of visual stimuli, enhancing discrimination relevant to task performance at the expense of other related discriminations,” explains first author Joe Schumacher. Now the lab has set its sights on combining this approach with new technologies to unlock the sequence and changes that occur in multiple types of neurons to mediate perceptual learning. By examining these questions in the tree shrew’s visual system, scientists in the Fitzpatrick lab are discovering fundamental new insights about perceptual learning that could influence our understanding of a wide variety of learning disabilities.
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