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Linear analysis of Previous: Parametric Mappings  Superposition
Assumption  The computational characteristics of each neuron are
not independent of the ones of other neurons laying in the same
layer, rather, they are often the consequence of a collective
behavior of neighboring cells. More specifically, one can assume
the superposition of feed-forward and feedback contributions to
investigate how information is processed through the various
stages of the visual pathway. At each stage, we can identify
components or computational primitives due only to feed-forward
connections (e.g., afferent projections) and the properties not
found in the components of a given stage can emerge from their
organization and their interactions with components of the
subsequent one. According to such principle, we assume that, at
cortical level, simple cell RF profiles are the consequence of
two main factors: (1) functional projections of LGN afferent
neurons and (2) intra