Who Needs Emotions? The Brain Meets the Robot

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approach to the social interactions stressed by Adolphs (Chapter 2). Indeed,
Jeannerod (Chapter 6) explores the possible role of mirror systems in empathy
and our ability to understand the emotions of others. However, I must
confess here that the current chapter will place most emphasis on the brainin-the-individual
approach and will conclude by giving a theory of robot
emotions grounded in the analysis of a robot going about its tasks in some
ecological niche, rather than emphasizing social interactions.
Vision Evolving
The year 1959 saw the publication of two great papers on the neurophysiology
of vertebrate vision: the study by Lettvin, Maturana, McCulloch, and
Pitts (1959) of feature detectors in the frog’s retina and that by Hubel and
Wiesel (1959) of receptive fields of neurons in the cat primary visual cortex.
We will analyze the first work in relation to later studies of frog behavior
(postponing a brief look at the role of motivation; we will then look at
the more generic coding in the cat visual system and ponder its implications.
Action-Oriented Feature Detectors in Frog Retina
Lettvin, Maturana, McCulloch, and Pitts (1959) studied “what the frog’s eye
tells the frog’s brain” and reported that frog ganglion cells (the output cells
of the retina) come in four varieties, each providing a retinotopic map of a
different feature to the tectum, the key visual region of the midbrain (the
homolog, or “evolutionary cousin,” of what in mammals is often referred to
as the “superior colliculus”):
1. The boundary detectors
2. The movement-gated, dark convex boundary detectors
3. The moving or changing contrast detectors
4. The dimming detectors
Indeed, axons of the cells of each group end in a separate layer of the
tectum but are in registration: points in different layers which are stacked
atop each other in the tectum correspond to the same small region of the
retina. All this shows that the function of the frog retina is not to transmit
information about the point-to-point pattern distribution of light upon it
but rather to analyze this image at every point in terms of boundaries, moving
curvatures, changing contrasts, and local dimming. Lettvin’s group argues
that the convexity detectors (operation 2 above) serve as “bug perceivers,”
while operation 4 could be thought of as providing “predator detectors.”