Reviewed by: Oliver Braddick, University of Oxford, Oxford, UK;
and Janette Atkinson, University College London, London, UK
Entering the topic “perceptual learning” into Web of Science returns over 100 publications
for every year since 2008, so it is clearly a hot topic. And that probably doesn’t
include
most of the deluge of papers which use machine learning to distinguish stimulus categories—an
endeavor which suggests the amazing potential of learning mechanisms and may provide
models
for human acquisition of perceptual abilities.
Kevin Connolly is a philosopher of mind, and he describes the aim of his book to “offer
an
empirically informed account of perceptual learning for philosophers.” The readership
of
Perception is not therefore his main target audience, but we can ask: how
well does he present empirical perceptual science to philosophers? And, does his philosophical
approach offer an analysis that is useful for empirical perceptual scientists?
Connolly has certainly done his homework on the empirical science—about 50% of the
references
cited are to studies in experimental psychology and neuroscience. However, in presenting
these
results, he does not necessarily convey the questions the scientists were asking.
The first
issue Connolly addresses is: “Does perceptual learning exist,” by which he means “Are
the
changes described by this term truly perceptual?” While he resoundingly refutes some
philosophers who have denied that they are, he sets a boundary on “perception” of
which we may
be sceptical or impatient. For instance, he cites experiments by Law and Gold (2008)
which found that the brain changes
when macaques learned to improve their motion coherence thresholds were in decision
processing
structures rather than early visual areas and concludes that this disqualifies the
learning in
this case from being “perceptual.” The result is significant, but the implied dividing
line
may be less so—the more we know about the brain networks linking vision to decision,
action,
and recognition, the more we recognize the essential continuity of these processes,
especially
given the ubiquitous feedback loops that infuse information from “higher” areas into
early
visual processing. So Connolly cites several lines of evidence that learning modifies
functional magnetic resonance imaging and electroencephalography responses in early
visual
cortex, but doesn’t ask from whence these effects find their way into early visual
cortex.
Questions about how the mechanisms of perceptual learning interface with the detailed
processes of vision do not figure strongly in the issues he considers.
Certainly, perceptual scientists don’t necessarily draw the dividing line in the same
place.
It is notable that Connolly doesn’t cite the work of Barbara Dosher and her colleagues
(Dosher & Lu, 2017) who conclude that
“reweighting evidence from one level to another of representation (of which their
major model
is reweighting the inputs to a decision process) or within levels is a major and perhaps
the
major form of perceptual learning.” However, Connolly’s arguments, developed at length
in
several chapters, do feature “attentional weighting” as a major component of perceptual
learning, so there is certainly scope for bridging the conceptual gap between the
disciplines.
Attentional weighting is only one of three types of process which Connolly proposes
as
species of perceptual learning. The other two are “unitization”—the combination of
elements
(within or between modalities) into an integrated representation, and “differentiation”—the
process of establishing distinct representations of two stimulus categories that are
initially
indistinguishable. From a mechanistic point of view, it is not clear how differentiation
differs from attentional reweighting—the learning process comes to select and amplify
the
internal signals which are different between the categories (and perhaps downregulate
those
that they have in common). But Connolly is more concerned with phenomenology than
mechanism
and spends a lot of time on issues such as whether we come to hear the
difference between homophone words such as “bank” (the financial institution) and
“bank” (the
edge of the river)—an instance of the “Phenomenal Contrast Argument” that is a target
for his
repeated refutation.
A surprising blind spot in Connolly’s account is early perceptual development. He
accepts an
assertion by Kellman and Garrigan that infants’ development of visual abilities arises
primarily from “innate or maturational” mechanisms and doesn’t count as perceptual
learning.
This does not set easily with his awareness of the plasticity of the visual system
in an
initial critical period, nor with (to take an example) the development of face perception
following the neonate’s sensitivity to a crude configuration, linked to intense exposure
to
human faces in the first months. Perhaps the problem is that babies don’t produce
a commentary
on their subjective visual experience, and develop vision in a way that is inextricably
entangled with their acquisition of physical and social concepts and of visuo-motor
skills.
Connolly’s discussion considers at various points the question of cognitive penetrability—how
far our perceptual processes can be accessed, and manipulated, by consciously willed
actions.
It is an important issue, at least if we want to understand the relation between consciousness
and the organization of the brain’s operation, and concerns psychologists and neuroscientists
as well as philosophers. For Connolly, it connects with a provocative and (to these
reviewers)
implausible proposal. He suggests that the function of perceptual learning is to offload
demands from slow, deliberate, and demanding cognitive processes to fast, automatic
and highly
parallel perceptual processes. This is a well-established idea in skill learning (remember
needing to think about the gear lever when you were learning to drive). However, in
the
context of perceptual learning, it suggests that before learning has occurred, the
judgments
involved can be laboriously made through cognitive effort. One of Connolly’s favored
examples
is learning to perceive the difference between different wines. Are we to believe
that the
novice can distinguish Chateau Lafite from Chateau Margaux, if only she thinks about
it long
and hard enough? Or that Law and Gold’s monkeys could have, but didn’t, use cognitive
processes to get their rewards for distinguishing 25% motion coherence early in their
testing?
Isn’t it good enough simply to suppose that we possess a potential learning process
that
enables us to see, hear, or taste differences that we simply couldn’t see, hear or
taste
before?
As perceptual scientists, we must welcome that philosophers of mind are bringing relevant
experimental evidence to bear on the questions they debate. And eavesdropping on their
debates
can and should provoke experimentalists to think harder about the meaning of their
results.
But a book such as this, in the end, reminds us that most of the time, we are asking
different
questions.