Autoencoding Developmental Change in Vision

The human visual system begins essentially as a "blank slate," with only architectural connections, specific distributions of neuron types, and only the most basic of visual preferences specified at birth (not coincidentally, a preference for faces).

One of the hypothesized developmental changes in vision takes the form of the "representational acuity hypothesis," by Westermann and Mareschal. According to this view, neural receptive fields narrow in size based on experience; this perspective enjoys correlational evidence from infants below the age of 6 months, who are better at discriminating the faces of non-human species than those older than 10 months. The perceptual representation of faces becomes tuned with experience.

Additional behavioral evidence for this developmental changes in visual feature processing comes from a task in which infants are exposed to animals varying along three features (body, tail, and feet), with each feature having one of three possible values (giraffe, cow, or elephant body; feathered, fluffy, or horse tail; webbed, clubbed, or hoofed feet). In experiment 1, every animal presented to the infants had a unique combination of features until they were no longe rinterested in the stimuli (habituation of looking time, a standard measure of familiarization). Then, the researchers showed them three new animals: one which the infants had seen previously, one which combined features from multiple different animals in the initial familiarization set, and one which had completely new features. While 4 month olds only "dishabituated" to the completely novel animal, 7 month olds also looked longer at the novel animal with features drawn from the familiarization set. This result suggests that 7 month olds, and not 4 month olds, represent and maintain the correlations between visual items - and therefore perform "relational processing." Subsequent experiments showed that 7 month olds are not as sensitive to specific correlations between features as 10 month olds, and that this difference is not merely an increased novelty preference among 10 month olds.

The authors implemented a demonstration of the "representational acuity account" of these "featural to relational" changes using a self-supervised autoencoding neural network model. Such networks have been used to model infant eye-gaze behaviors, in which looking time is determined by the sum of squared errors between the input pattern and the "reconstructed" or "autoencoded" output pattern; the more error, the longer the looking times. These researchers used a Gaussian activation function as opposed to the standard sigmoid, and only the hidden-to-output weights were modified during learning. Although previous models had successfully simulated the performance of infants on a looking-time task, they had used unrealistic "batch" training input. In contrast, the current model was trained on real cases in sequence, locally coded as the presence or absence of specific feature types.

This model, like the previous ones, successfully simulated 10 month old infant behavior. But, by gradually changing the size of the receptive fields in the hidden layer, the authors were also able to simulate the behavioral results seen in 7 and even in 4 month olds. This is taken as evidence that changes in receptive field size are a sufficient mechanism to explain the developmental shift from featural to relational visual processing.

However, as the researchers admit, this account is a kind of "cheat" - the exact mechanisms guiding receptive field size change were not explicitly modeled. They offer two possibilities: internally generated neural activity ("noise") may decrease receptive field size, or unrelated external events may cause the receptive fields to shrink.

The models motivate further predictions: 4 month olds may actually be capable of showing relational processing if the features are sufficiently distinct from one another. According to the authors, preliminary evidence from Younger's lab suggests that strongly contrasting colors can actually encourage this behavior among 4 month olds. Second, the transition between these behaviors may appear to be rapid, but is really the result of more gradual underlying representational change. As in competing memory systems accounts of task-switching, different representations may compete for dominance in attentional networks, and at crucial developmental breakpoints can show extreme sensitivity to relatively slight changes in salience.

Related Posts:
Functional Anatomy of Visual Short Term Memory
Task Switching in Prefrontal Cortex
Learning Like a Child
Tuned and Pruned: Synaesthesia


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