Constructing visual function through prenatal and postnatal learning

Abstract

Although environment-driven learning can explain much of postnatal neural development, substantial organization and functional ability is present even at birth. Recent experimental discoveries of widespread spontaneous neural activity suggest that prenatal development may utilize very similar mechanisms and principles as postnatal learning, driven by internally generated sources instead of the environment. This chapter shows how this idea can explain features of the organization and function of the primary visual cortex (V1) and higher level face-processing areas. Specifically, we simulate how neural preferences for contour orientation and human faces can develop prenatally from internally generated activity and postnatally from natural image stimuli. These simulations are based on HLISSOM, a hierarchical self-organizing model of the development of topographic neural maps. The results match experimental neuroimaging and psychophysical data from newborn and older animals and humans, and provide concrete predictions about infant behavior and neural activity for future experiments. They also suggest that combining internally generated activity with a learning algorithm is an efficient way to develop complex neural machinery.

A Geometric Model of Multi-scale Orientation Preference Maps via Gabor Functions

“…al. [38], Bednar and Miikkulainen [5]). A refinement of the orientation maps is performed subsequently by activation patterns based on random waves (see the results provided by Cang et.…”

“…Secondly we start from a noise generated on the real domain and apply a Bargmann transform, while the other method introduces the noise in the Fourier domain on the irreducible representations, and apply the Bargmann transform in the Fourier space. The choice made in the present paper here is physiologically more plausible since experimentally cortical maps can arise in the early post natal period in absence of any external stimulus just in presence of a random basal activation (see Bednar and Miikkulainen [5] and Jegelka et. al.…”

How Infants Learn About the Visual World

“…This might be one way by which correlated inputs remain coupled and dissimilar inputs become dissociated, and a likely means by which edges (which can be defined as simple, local interactions in the input) can be detected upon exposure to patterned visual scenes (Albert, Schnabel, & Field, 2008). Retinal waves also can serve as a foundation for development of representations of more complex visual patterns as infants gain exposure to the environment (Bednar & Miikkulainen, 2007).…”

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

“…Put concretely, the parameter changes reported in Table A1 were all implemented "by hand" for the present simulations. It will be important in future efforts to probe whether such changes can emerge from, for instance, Hebbian processes involved in the tuning of cortical maps (Bednar & Miikkulainen, 2007;Kohonen, 1982;Miikkulainen, et al, 1999). We have taken steps in this direction by implementing a reference frame alignment and calibration process in the "adult" model .…”