Perceptual Learning
Two football players on a field. The football is on the field with the player closest to the ball in blue and the other one in orange.
What is perceptual learning? This type of learning refers to a general class of phenomena related to improved performance stemming from training or practice in perceptual tasks (Lu et al., 2009). Perceptual learning is a lifelong process and it begins by encoding information about the basic structure of the natural world and continues throughout life as we assimilate information about familiar specific patterns (Gilbert, 2001). This type of learning has also been observed in all the human senses - vision, hearing, touch, taste, and smell - thus providing evidence that experiences can improve human performance on perceptual tasks (Maniglia & Seitz, 2018). Okay, so what does this all mean? Perceptual learning is a learning process that happens via experience and practice leading to long term improvements in one’s ability to perceive and interpret sensory information. Here are two examples. The first is a musician learning to distinguish between the subtle differences between musical pitches. The second is a soccer player learning to pay attention to an opponent's hip articulation in their movements, which represents experience-dependent enhancement of sensory perception.
In the early years, the role of learning in perception was vigorously denied by early Gestalt psychologists and it wasn’t until 1969 that Eleanor J. Gibson published the first book on perceptual learning describing this type of learning as a process of discovering how to transform overlooked sensory stimulation potentials into effective information (Lu et al., 2009). Now there is a keen interest in studying perceptual learning.
Perceptual learning includes things like: distinguishing between different odors or musical pitches or discriminating between different shades of colors. Going back all the way to infancy, they use perceptual information to inform what choices they make about their motor actions (Adolph & Joh, 2007). As an example, infants may adjust their crawling or walking in response to rigidity, slipperiness, or slant of surfaces (Adolph, 1997). Furthermore, most of the perceptual information infants receive comes from motor movements like the movements of the eyes, arms, legs, and hands (Adolph & Berger, 2006).
Because different forms of learning differ in which brain regions they are represented, the underlying mechanisms of the forms of memory have the potential to be quite similar at the level of signal transduction cascades and circuitry (Gilbert, 2001). Based on that understanding, perceptual learning is being used as the basis for understanding the mechanisms in general as it involves cortical areas at the early states of visual processing (Gilber, 2001). This is where one of my favorite neuroscience concepts comes into play, neuroplasticity, which we won’t be focusing on today - but we will come back to it!
Neuroscience of Perceptual Learning
You can absolutely skip this section if you are tired of neuroscience. The adult primary visual cortex (V1), once thought to only have the ability to undergo change in the first months to years of life, continues to show the ability to evolve and change even in adulthood (aka. neuroplasticity) (Gilbert et al., 2001; Maniglia & Seitz, 2018). This idea is important to keep in mind as we continue with this discussion, as this is one part of the brain that is involved in perceptual learning. What has also been revealed is that perceptual learning has also been shown to affect even earlier, pre-cortical neural loci, specifically the Lateral Geniculate Nucleus (Maniglia & Seitz, 2018). While the primary visual cortex (V1) gets the most attention, there are other visual processing areas that are involved and show unique patterns of featural sensitivity. For example (Maniglia & Seitz, 2018):
Middle temporal visual area (MT or V5) to motion.
Region of extrastriate visual cortex.
Visual area (V4) to curvature and color.
One of the visual areas in the extrastriate visual cortex.
Fusiform face area (FFA) to faces.
Part of the human visual system that is specialized for facial recognition.
The FFA is located in the inferior temporal cortex (IT), in the fusiform gyrus (Brodmann area 37).
Parahippocampal place area (PPA) to houses and scenes.
Sub-region of the parahippocampal cortex that lies medially in the inferior temporo-occipital cortex.
Plays an important role in the encoding and recognition of environmental scenes.
What is fascinating about all this is that many perceptual learning studies train with stimulus features like shapes, objects, and faces, all of which plasticity in the primary visual cortex would not be sufficient to account for the learning (Maniglia & Seitz, 2018).
Theories and Mechanisms
It is important to look at the theories of the mechanisms that occur within the brain and what approaches are being used. There are three approaches of interest: inferences from behavior, combination of measures of behavior and brain activity, and a combination of measuring of brain activity and behavior in non-human subjects (Gold et al., 2001).
The first approach of inferences from behavior combines different ideas. Because of the specificity of perceptual learning to the stimulus configuration used during trainings, the argument has been made that the changes must occur in the early areas of the sensory cortex. However, it has been noted that this is not the only possibility because more central changes could also exhibit specificity. Outside of this approach is another theory, the reverse hierarchy theory, which interprets attention-related differences in perceptual learning in terms of different loci of learning moving from higher to lower processing levels in the brain. It has also been suggested that the key attentional subsystem is related to altering instead of orienting executive function, which helps tag stimulus features that need to be learned. This thought helps explain higher brain areas involvement and the learning of task-irrelevant features (Gold et al., 2001).
The second approach that combines the measurement of behavior and brain activity uses non-invasive techniques. What has been learned out of this approach, for example, is that there is a connection between the primary visual cortex and the retinotopic location of a trained visual stimulus after perceptual learning. Another two are the importance of sleep and that there is more involved than just the early visual areas, such as the parietal cortex, which suggests that there are higher areas involved in this type of learning (Gold et al., 2001).
The third approach that combines the measurement of brain activity and behavior in non-human subjects has identified some interesting information. There have been studies that identified changes in the primary auditory and somatosensory cortices of monkeys as well as similar changes in the visual pathway. Though, the changes found in the primary visual cortex were small relative to those found in the auditory and somatosensory cortex (Gold et al., 2001).
One last piece of interesting information before switching gears. As with many systems, there are perceptual inefficiencies. According to Lu et al. (2009), the inefficiencies can be attributed to three limitations in perceptual processes.
An imperfect perceptual template
Internal additive noise
Multiplicative noise
Lu et al. (2009) use this information to distinguish three mechanisms of perceptual learning:
External noise exclusion
Stimulus enhancement
Internal multiplicative noise reduction
So what does all this mean? To bring everything back around, neural correlates have been identified for only a small fraction of behavioral perceptual learning phenomena (Gold et al., 2001). Put bluntly, there is much more to learn and we don’t have a very clear picture of perceptual learning.
Cultural Differences
Everyday we live in a culture and it shapes our brains and behaviors which means that people from various cultures process the world differently (Psychneuro, 2016). Furthermore, culture creates an environment of a shared belief, way of thinking, and method among the people (Psychneuro, 2016). Taking it a step further to what a wonderful teacher once taught me, we are also a microculture of one. No one else has our exact experiences. As far as I am aware people don’t even experience the same events in the exact same way. Keeping that in mind, perceptual learning ties into culture and diversity without a doubt.
Gender, race, sexual orientation, ability, class, nationality, and age all impact perceptions and the schemata through which we interpret what we perceive are influenced by all these identities (Lumen Learning, n.d.). As people are socialized into different cultural identities, these beliefs are internalized. As discussed above, perception starts with information that enters through the five senses and how we perceive this basic sensory information is influenced by culture. For example, Americans consider masking body odor important because we find it unpleasant. In other cultures, they may not mind body odor or even notice it and find the smell of cleanliness unpleasant.
take action today moment:
How does perceptual learning show up in your life? Why might it be important for you to consider when it comes to learning a new skill? Take some time to consider these questions.
Learn More About perceptual learning:
52 – Perceptual Learning I: Introduction (Podcast on YouTube)
53 – Perceptual Learning II – Direct Learning (Podcast on YouTube)
54 – Perceptual Learning III: Application to Sports (Podcast on YouTube)
Vagus Nerve Stimulation Can Boost Perceptual Learning
References
Adolph, K. E. (1997). Learning in the development of infant Locomotion. Monographs of the Society for Research in Child Development, 62(3), i–162. https://doi.org/10.2307/1166199
Adolph, K. E., & Berger, S. E. (2006). Motor Development. In D. Kuhn, R. S. Siegler, W. Damon, & R. M. Lerner (Eds.), Handbook of child psychology: Cognition, perception, and language (pp. 161–213). John Wiley & Sons Inc.
Adolph, K., & Joh, A. S. (2007). Motor development: How infants get into the act. In A. Slater, & M. Lewis (Eds.), Introduction to infant development (2nd ed., pp. 63-80). Oxford University Press.
Gilbert, C. D., Sigman, M., & Crist, R. E. (2001). The neural basis of perceptual learning. Neuron, 31(5), 681-697. https://doi.org/10.1016/S0896-6273(01)00424-X
Gold, J. I., & Watanabe, T. (2010). Perceptual learning. Current Biology, 20(2), R46–R48. https://doi.org/10.1016/j.cub.2009.10.066
Lu, Z. L., & Dosher, B. A. (2009). Mechanisms of perceptual learning. Learning & Perception, 1(1), 19–36. https://doi.org/10.1556/LP.1.2009.1.3
Lu, Z. L., Yu, C., Watanabe, T., Sagi, D., & Levi, D. (2009). Perceptual learning: functions, mechanisms, and applications. Vision Research, 49(21), 2531–2534. https://doi.org/10.1016/j.visres.2009.09.023
Lumen Learning. (n.d.). Culture, personality, and perception. https://courses.lumenlearning.com/atdcoursereview-speechcomm-1/chapter/culture-personality-and-perception/
Maniglia, M., & Seitz, A. R. (2018). Towards a whole brain model of perceptual learning. Current Opinion in Behavioral Sciences, 20, 47–55. https://doi.org/10.1016/j.cobeha.2017.10.004
Psychneuro (2016, February 17). Culture’s influence of perception. On psychology and neuroscience. https://psych-neuro.com/2016/02/17/cultures-influence-on-perception/