In a not very distant past, very few
people would dispute what I will call the Perception Dogma, or the dogma for
short. Say that we focus on visual perception. The idea was that a certain
information would be registered at the retina, then the result of such a
process would be sent on up to the primary visual cortex, and then up to
associative areas until some sort of representation was formed in some part of
Common to all variations on this
view of perception, there was a clear distinction between some sort of
“primary” stage, that was called sensation, and a cognitive one that was called
perception. More concretely, the transduction of physical energy (e.g., light,
sound, pressure, etc.) in the environment into neural signals and codes would
correspond to sensation. This would have to be distinguished from the
interpretation of those signals and codes, which is what would correspond to
perception. Thus, while we would sense lights, sounds, tastes, smells
and touches, we would perceive them as, say, a chocolate ice-cream
or a glass of lightly chilled Burgundy.
It seems now without question that
contemporary neuroscience is changing such a view, not only in relation with
visual perception, but also in all sensory modalities. The research that is
being conducted in developmental neurobiology, neurophysiology and cognitive
neuropsychology is suggesting that the processes involved in perception are so
intermingled that there is little value in trying to divide them up neatly into
sensation and perception. Among other things, the research has shown that there
is a strong processing of feed back processing of information between final and
initial stages of the perceptual process, as well as between different sensory
modalities. In short, the evidence
blurs the boundaries between sensations and perceptions.
The present paper is divided in two
parts. In the first one I will present recent evidence that is changing
completely the traditional way of characterizing perception. In the second
part, to be published shortly, I will outline the elements for a new conceptualization
Unidirectionality of perception?
Neuroanatomists have always known
that there are massive feedback pathways projecting from “higher”, associative,
cortical areas to “lower”, primary, cortical areas. True, the anatomy and
physiology of the details of connections among all the different perceptual
areas are still subject of intense investigation. Nevertheless, it is a fact
that anatomical research has shown that, for example, the ascending pathways
from the retinal to the geniculate nucleus and from there to the visual
cortices and to other centers higher in the processing hierarchy are matched by
descending pathways from the higher level of processing to even the earliest
processing systems at the retina (Zeki 1978; Van Essen 1985). Additionally, the
mammalian visual system has been seen to consist of a large number of cortical
areas which that are interconnected by many pathways, some of which can be
characterized as bottom-up, and others as top-down (Felleman and
Van Essen, 1991). Moreover, the bottom-up
projections constitute only a small minority of all synapses into cortical
areas, whereas the top-down connections seem to be more abundant and
diffuse (König and Luksch 1998; Douglas and Martin 1998).
However, these anatomical facts have
been greatly ignored from the point of view of perceptual processing. At most,
it has been proposed that such feed-back projections served only as a sort of
modulating influence. This is so because, according to a dogma’s hypothesis known as the impenetrability thesis of
perception (Fodor 1983), perception is a bottom-up process and cannot receive
top-down influences. The hypothesis asserts that higher cognitive processes,
the systems of belief and knowledge, have little or no impact on processing in
sensory-motor systems, because sensory systems are impenetrable.
Contrary to this conclusion,
however, recent evidence indicates that higher cortical areas affect the
content of sensory-motor systems directly. The primary cortex is not
anymore a mere relay station when certain information is processed and
re-directed to other parts of the cortex. There is a dynamic interplay between
the brain’s so-called early sensory areas and the higher perceptual centers. In
this sense, recent experiments in awake behaving animals (von Stein et al 1997)
have shown that the coupling between different levels of visual perceptual
areas depends on the expectancy of the individual. In particular, a feedback
interaction in form of increased synchronization was found between primary
visual areas and associative areas. The functional mechanism and the
consequences of the interactions remain unclear, but it seems that primary
visual areas can, and may need, be influenced by associative areas to function
properly (Gilbert 1998).
In humans, studies (Zacks et al
2001) suggest that the perception of certain high-level stimulus need the
simultaneous activity in primary regions (the extrastriate motion area MT or
V5), and higher associative areas (the frontal eye fields, FEF). This research
has tapped into a network of brain processes that involves top-down
expectations and bottom-up motion cues
as a simultaneous processing. All these processes may contribute to the ability
to form perceptual distinctions, and favor a top-down interpretation in which
perception is determined by knowledge of the stimuli.
Additionally, neuroscience research
on mental imagery has demonstrated that the primary visual cortex, V1, is often
active, along with many other early visual areas (e.g., Kosslyn et al 1995). In
motor imagery, the primary motor cortex, M1, is often active, along with many
other early motor areas (e.g., Crammond 1997; Deschaumes-Molinaro et al
1992; Jeannerod 1994, 1995). Indeed, motor imagery not only activates early
motor areas, it also stimulates spinal neurons, produces limb movements, and
modulates both respiration and heart rate. For example, when proficient
shooters imagine shooting a gun their entire body behaves similarly to actually
doing so. In auditory imagery, activation has been observed in the primary
auditory cortex (Calvert et al 1997) and activation has been observed in other
early auditory areas (e.g., Zatorre et al 1996).
Memory also seems to play an active
role in perception. Considerable evidence suggests that specific experience
early in life can influence the perceptual processing of basic perceptual
stimuli, such as orientation and tilt, in visual perception, or auditory
illusions (Blakemore & Cooper1970; Sengpiel et al 1999; Merzenich
et al. 1984; Gilbert and Wiesel 1992; Darian-Smith &
Gilbert1994; Gilbert et al 1996; Whitaker and McGraw). Likewise, in perceptual
anticipation, the cognitive system uses past experience to simulate a perceived
entity's future activity. For example, if an object traveling along a trajectory
disappears, perceivers anticipate where it would be if it were still on the
trajectory, recognizing it faster at this point than at the point it
disappeared, or at any other point in the display. Recent findings indicate
that knowledge affects the simulation of these trajectories. When subjects
believe that an ambiguous object is a rocket, they simulate a different
trajectory compared to when they believe it is a steeple (Reed & Vinson
1996). Even infants produce perceptual anticipations in various occlusion tasks
(Hespos & Rochat 1997).
Research studies by Karni and Sagi
(1995), Yeo, Yonebayashi, and Allman (1995), Antonini, Strycker, and Chapman
(1995), Stiles (1995), Merzenich and Jenkins (1995) also show that changes can
be induced in visual cortical neural patterns in response to learning. In other
words, visual processing at all levels may undergo long-term,
experience-dependent changes. One type of learning is known as “slow learning”.
This type of learning causes structural changes in the cortex, with formation of new patterns of connectivity.
Such a learning can result in significant performance improvement; for example,
one may learn with practice to perform better at visual skills involving target
and texture discrimination and target detection, and to learn to identify
visual patterns in fragmented residues of whole patterns (priming). Performance
in these tasks was thought to be determined by low-level, stimulus-dependent
visual processing stages. The improvement in performance in these tasks, thus,
suggests that practice may modify the adult visual system, even at the early
levels of processing. As Karni and Sagi remark “[L]earning (acquisition) and
memory (retention) of visual skills would occur at the earliest level within
the visual processing stream where the minimally sufficient neuronal computing
capability is available for representing stimulus parameters that are relevant
input for the performance of a specific task” (1995, pp.95–6).
All of these results reinforce the
idea that perception cannot be seen as a bottom-up process in which each stage
is independent of the next. The results further indicate that top-down
and bottom-up processes coordinate the processing of useful perceptions.
Domain-specificity of perception?
Many textbooks on perception
consider each sensory modality -vision, hearing, etc.- in isolation, as if each
modality processed its information without relevant interactions with other
senses. However, integration among
different modalities is not only a common phenomenon in the brain, but it is
also prerequisite for many types of perception and behavior. Of course, nobody questions that at some
level there is some sort of integration between different modalities (such as
that the concept [rose] could include visual and olfactory cues). The dogma
asserts that the sensory processing respects modality boundaries. This is
sometimes referred to the modularity hypothesis (Fodor 1983).
The word "module" is a
sort of battle field for many cognitive theorists. As it is recognized by
nearly everybody, the term “module” is used in markedly different ways by
different schools of thought and by different scientific disciplines. This fact
has not helped the interdisciplinary discussions of cognition. In neuroscientific terms, a "module"
refers to some neuroanatomical characteristics in which brains are structured,
with cells, columns, layers and/or regions that divide up the labor of
information processing in a variety of ways.
In cognitive science and
linguistics, the term "module" refers to another view, which is
normally attributed to Jerry Fodor's (1983).
A Fodorian module is a specialized, encapsulated mental sub-system that
has evolved to handle specific information.
Fodor argues that perceptual sub-systems are one of such a structure,
and lists a number of properties which are characteristic of a cognitive
system's being modular, the most important of which are: (i) informational
encapsulation (i.e., modules have little or no access to the background beliefs
and goals of the larger organism), (ii) domain specificity, (iii)
unconsciousness (modules provide very limited information about the processing
steps) and (iv) innateness. There are
other criteria which does not interest us here, such as speed of processing
(modules are very fast), obligatory
firing (modules operate reflexively, providing pre-determined outputs for
pre-determined inputs regardless of the context), ontogenetic universals (i.e. modules develop
in a characteristic sequence), localization (i.e. modules are mediated by
dedicated neural systems), and pathological universals (i.e. modules break down
in a characteristic fashion following some insult to the system).
The claim in Fodor's version of
modularity about information encapsulation and domain-specificity of
perceptual sub-systems is contradicted by recent neurophysiological and
neuropsychological evidence. There are many research results that show that the
very sensory processing of each modality interacts normally with other
Crossmodal integration of
multisensory cues (for instance, visual and auditory) is one of these examples.
In the crossmodal integration two or more modalities are integrated in the same
process. Many research results suggest that crossmodal integration is not only
a fact, but it is also necessary in perceptual processing in early stages
(Driver 1996; Vroomen and Gelder 2000; Macaluso et al 2000).
One of the most famous examples is
the McGurk effect, where seen lip-movements can alter which phoneme is heard
for a particular sound, while in the ventriloquism effect, they can alter the
apparent location of speech sounds.
A recent study in humans (Calvert et
al 1997) has also shown that perceiving a speaker’s lips during face-to-face
conversation (lip-reading) activates auditory cortex in normal hearing
individuals in the absence of auditory speech sounds. Moreover, the experiments carried out by Calvert and colleagues
suggest that these auditory cortical areas are not engaged when an individual
is viewing nonlinguistic facial movements but appear to be activated by silent
meaningless speechlike movements (pseudospeech). In other words, these
experiments suggest that silent lip-reading activates auditory cortical
sites also engaged during the perception of heard speech. This supports
psycholinguistic evidence that seen speech influences the perception of heard
speech at a prelexical stage.
The crossmodal effects are not
restricted to the auditory modalities. Among others, there have been studies
that found that the superior colliculi integrates cues from three sensory
modalities, vision, audition and somatosensation (Wallace et al 1996; Sparks
& Groh 1995), and others experiments show that visual perception can be
qualitatively altered by sound (Shams et al 2000). The ventriloquist
effect can also be obtained by visual
and tactile cues (Radeau 1994; Spence,
Driver 2000; Pavani, Spence, Driver
2000). Likewise, the McGurk-like effects happens with for non-speech
stimuli, as when both hearing and seeing musical instruments (Saldaña and
Rosenblum 1993). Perturbing the sounds made as hands are rubbed together can
affect the perception of skin texture, while changing the color of drinks or
food can alter the perception of their flavor
(Jousmäki, Hari 1998; DuBose, Cardello, Maller 1980).
As for the chemical senses studies
reveal perceptual processes responsive to combinations of odors and tastes
(Gielen et al 1983; Stevens, 1997; Guadagni et al 1963; Murphy 1977). One of the best examples of such an
integrative process may be flavor perception, whereby activation in two
peripherally distinct neural systems, olfaction and gustation, combines to give
rise to an unified perception. It has been argued that the integration may
happen in a post-sensory stage, but recent studies show that crossmodal
summation of subthreshold concentrations of selected gustatory and olfactory
stimuli happen at the very early stages of the perceptual processing, thus
demonstrating that integration of taste and smell occur all along the
perceptual processing (Dalton et al 2000). Crossmodal integration seems to be
the rule rather than the exception.
Finally, there are recent studies
that are even more intriguing, since they suggest that all perceptual processes
can be modulated and affected by emotional cues. In short, perceptions may be
influenced by the emotional significance of an impinging stimulus. Adam
Anderson and Elizabeth Phelps (2001) have shown that the amygdala supports
emotional influences directly on
perception itself. Their research shows for the first time that
perceptual systems are exquisitely tuned to the occurrence of emotionally
significant stimulus events, requiring much less attention or effort to reach
conscious awareness compared to events of neutral value.
Boundaries between perception and
But there is more. Not only top-down
influences on perceptual processes are normal, but even (dogmatic) perceptual
abilities can be performed by (dogmatic) sensory processes. A recent study
(Freedman et al 2001) pose, for example, a major problem for current models of
visual processing. In particular, it implies that a great deal of
categorization processing can be done on the basis of the perceptual visual
sub-systems. Freedman and colleagues examined the responses of neurons in the
prefrontal cortex (PFC) of monkeys trained to categorize animal forms
(generated by computer) as either "doglike" or "catlike."
By continuously "morphing" the basic form of one animal into the
other, the authors were able to identify
neurons that responded to category membership rather than simple
processing of the physical characteristics of the images.
One of the most impressive features
of their research is the speed at which the categorization responses took
place. Monkeys categorized stimuli very
quickly, with reaction times that average 250 to 260 milliseconds but that can
be as short as 180 milliseconds. The areas implicated were the lateral
geniculate nucleus of the thalamus (LGN), V1, the so-called primary visual
cortex, areas V2 and V4 of the ventral visual pathway, areas in the posterior and anterior inferior
temporal cortex (ITC) and the prefrontal cortex (PFC). This does not allow much
time for complex iterative processing and suggests that the initial activation
of cells in ITC and PFC could depend largely on a feed-forward pass through the
visual system. This kind of data has strong implications for our understanding
of visual processing because it implies that the visual pathway must be acting
as a sort of pipeline processor, with different images being processed
simultaneously at different levels of the system.
Likewise, recent research shows that
even the systems of belief, knowledge, attention and consciousness modulate
perception. For example, conceptual representation of an ambiguous perceptual
stimulus biases sensory processing. In audition, when subjects believe that
multiple speakers are producing a series of speech sounds, they normalize the
sounds associated with each speaker (Magnuson & Nusbaum, 1993). In
contrast, when subjects believe that only one speaker is producing these same
sounds, they do not normalize them, treating them instead as differences in the
speaker's emphasis. Thus, each interpretation produces sensory processing that
is appropriate for its particular conceptualization of the world. Again,
cognition and sensation coordinate to produce meaningful perceptions.
Analogous interpretative effects
occur in vision. Conceptual interpretations guide computations of figure and
ground in early visual processing (Peterson & Gibson 1993); they affect the
selective adaptation of spatial frequency detectors (Weisstein & Harris
1980); and they facilitate edge detection (Weisstein & Harris 1974). Frith
and Dolan (1997) report that top-down interpretative processing activates
sensory-motor regions in the brain.
In sum, we have seen a number of
empirical studies that show three ways in which the dogmatic perceptual
framework loses ground. First, we have seen that perception is influenced by a
top-down flow of information, which intervenes in many different functional
directions. Secondly, we have seen how crossmodal sensory integrations is not
only a fact, but it may be even a requirement.
Finally, there may be some cases in which higher cognitive activities,
such as categorization, are performed in the very same perceptual
processing. The conclusion could not be
more clear: A new conceptualization of perceptual processes is called for.
Alston, W. P. (1993). The Reliability of Sense
Perception. Ithaca, NY: Cornell University Press.
Anderson A.K., Phelps E.A. (2001). Lesions of the human amygdala impair
enhanced perception of emotionally salient events. Nature 411: 305 -
Antonini, A., Strycker, M. P., & Chapman, B. (1995). Development and
plasticity of cortical columns and their thalamic inputs. In B. Julesz and I.
Kovacs (Eds.), Maturational windows and adult cortical plasticity. Reading,
Arbib, M.A., Erdi, P. and Szentágothai, J. 1997, Neural Organization:
Structure, Function, and Dynamics, Cambridge, MA: The MIT Press
Armstrong, D. M. (1961). Perception and the Physical World. London:
Austin, J. L., (1962). Sense and Sensibilia. London: Oxford University
Ayer, A. J., (1946-7). Phenomenalism, Proceedings of the
Aristotelian Society, 47: 163-96.
Barsalou, L.W. (1999). Perceptual symbol systems. Behavioral and
Brain Sciences, 22: 577-609.
Blakemore, C. & Cooper, G. F. (1970) Nature 228: 477–478
Calvert, G.A., Bullmore, E.T.,
Brammer, M.J., Campbell, R., Williams, S.C.R., McGuire, P.K, Woodruff, P.W.R.,
Iversen, S.D.S, David, A.S. (1997) Activation of Auditory Cortex During Silent
Lipreading. Science 276: 593-596.
Crammond, D.J. (1997). Motor imagery: Never in your wildest dreams.
Trends in Neuroscience, 20, 54-57.
Dalton, P., Doolittle, N., Nagata, H. and Breslin, P.A.S. (2000). The
merging of the senses: integration of subthreshold taste and smell. Nature
neuroscience 3: 431-432.
Darian-Smith, C. & Gilbert, C. D (1994) Nature 368: 737–740.
DeLancey, C. (1997). Emotion and the computational theory of mind. In
(S. O'Nuillain, P. McKevitt, & E. MacAogain, eds) Two Sciences of Mind.
Deschaumes-Molinaro, C., Dittmar, A., & Vernet-Maury, E.
(1992). Autonomic nervous system response patterns correlate with mental
imagery. Physiology & Behavior, 51, 1021-1027.
De Sousa, R. (1987). The rationality of emotion. Cambridge, MA: MIT
Donald, M. (1991). Origins of
the Modern Mind: Three stages in the evolution of culture and cognition.
Cambridge: Harvard University Press.
Douglas RJ, Martin KAC (1998). Neocortex. In: The synaptic organisation
of the brain (Shepherd GM ed), pp 389-438. New York: Oxford University
Driver J (1996). Enhancement of selective listening by illusory
mislocation of speech sounds due to lip-reading. Nature 381:66-68.
DuBose, C.N., Cardello A.V., Maller, O. (1980). Effects of colorants and
flavorants on identification, perceived flavor intensity, and hedonic quality
of fruit-flavored beverages and cake. J Food Sci 45:1393-1399.
Felleman D.J., Van Essen D.C. (1991) Distributed hierarchical processing
in the primate cerebral cortex. Cereb.Cortex. 1:1-47.
Freedman, D.J, Riesenhuber, M., Poggio, T. and Miller, E.K (2001).
Categorical Representation of Visual Stimuli in the Primate Prefrontal Cortex. Science
Frith, C., & Dolan, R.J. (1997). Brain mechanisms associated with
top-down processes in perception. Philosophical Transactions of the Royal
Society of London, Series B: Biological sciences, 352, 1221-1230.
Gao, J.H., Parsons, L.M, Bower, J.M, Xiong, J., Li, J., and Fox, P.T.
(1996). Science 272, 545-547.
Gielen, S. C., Schmidt, R. A. & Van Der Heuvel, P. J. (1983). Neural
and behavioral response enhancements to combinations of sensory stimuli are
found within and across many sensory
Percept. Psychophys. 34:161–168
Gilbert C.D. (1998) Adult cortical dynamics. Physiol.Rev. 78:467-485.
Gilbert, C. D. & Wiesel, T. N. (1992). Nature 356: 150–152.
Gilbert, C. D., Das, A., Ito, M., Kapadia, M. & Westheimer, G.
(1996). Proc. Natl. Acad.
Sci. USA 93: 615–622.
Gordon, R. M. (1987). The Structure of Emotions: Investigations in
Cognitive Philosophy. Cambridge University Press.
Guadagni, D. G., Buttery, R. G., Okano, S. & Burr, H. K. (1963) Nature
Hespos, S.J., & Rochat, P. (1997). Dynamic mental representation in
infancy. Cognition, 64, 153-188.
Jeannerod, M. (1995). Mental imagery in the motor context.
Neuropsychologia, 33, 1419-1432.
Jeannerod, M. (1994). The representing brain: Neural correlates of motor
intention and imagery. Behavioral and Brain Sciences, 17, 187-245.
Johnson, M. (1987). The Body in the Mind. Chicago: University of
Jousmäki V, Hari R (1998). Parchment-skin illusion: sound-biased touch. Curr
Karni, A., & Sagi, D. (1995). A memory system in the adult visual
cortex. In B. Julesz and I. Kovacs (Eds.), Maturational windows and adult
cortical plasticity. Reading, MA: Addison-Wesley.
König P, Luksch H (1998) Active sensing - closing multiple loops.
Zeitschrift für Naturforschung in press
Kosslyn, S.M., Thompson, W.L., Kim, I.J., & Alpert, N.M. (1995).
Topographical representations of mental images in primary visual cortex. Nature
Macaluso E, Frith C, Driver J (2000). Modulation of human visual cortex
by crossmodal spatial attention. Science 289: 1206-1208.
Magnuson, J.S., & Nusbaum, H.C. (1993). Talker differences and
perceptual normalization. Journal of theAcoustical Society of America, 93,
Merzenich, M. M. et al. (1984). J Comp Neurol 224: 591–605.
Merzenich, M. M., & Jenkins, W. M. (1995). Cortical plasticity,
learning, and learning dysfunction. In B. Julesz and I. Kovacs (Eds.), Maturational
windows and adult cortical plasticity. Reading, MA: Addison-Wesley.
Murphy, C., Cain, W. S. & Bartoshuk, L. M. (1977). Sens Process 1,
Nelson, K. (1985). Making sense. The Acquisition of Shared
Meaning. New York: Academic Press.
Nelson, K. (1996). Language in Cognitive Development. Emergence of
the Mediated Mind. Cambridge: Cambridge University Press.
Oatley, K. (1992). Best laid schemes: The psychology of emotions.
Cambridge: Cambridge University Press.
Pascual-Leone, A. and Walsh, V. (2001) Fast Backprojections from the Motion
to the Primary Visual Area Necessary for Visual Awareness. Science 292:
Pavani F, Spence C, Driver J
(2000). Visual capture of touch; out-of-the-body experiences with rubber
gloves. Psychol Sci (in press).
Peterson, M.A., & Gibson, B.S. (1993). Shape recognition inputs to
figure-ground organization in three-dimensional displays. Cognitive
Psychology, 3, 383-429.
Radeau M (1994). Auditory-visual spatial interaction and modularity. Curr
Psychol Cogn 13:3-51.
Raftopoulos, A. (2001). Is perception informationally encapsulated? The
issue of the theory-ladenness of perception. Cognitive Science 25:
Reed, C.L., & Vinson, N.G. (1996). Conceptual effects on
representational momentum. Journal of Experimental Psychology: Human Perception
and Performance, 22, 839-850.
Saldaña HM, Rosenblum LD (1993) Visual influences on auditory pluck and
bow judgments. Percept Psychophys 54: 406-416.
Sengpiel, F., Stawinski, P. & Bonhoeffer, T. (1999) Nat Neurosci 2:
Shams, L., Kamitani, Y. and Shimojo, S. (2000). What you see is what you
hear. Nature 408: 788.
Sparks, D. L. & Groh, J. M. (1995) in M. Gazzaniga (ed.) The
Cognitive Neurosciences MIT Press, Cambridge, Massachusetts.
Spence C, Driver J (2000). Attracting attention to the illusory location
of a sound: reflexive crossmodal orienting and ventriloquism. NeuroReport 11:
Von Stein A, Chiang C, König P (1997) The effect of experience and
behavior on interareal interactions. Soc Neurosci Abstr 23: 405.4
Stevens, J. C. (1997). Physiol. Behav. 62: 1137–1143.
Stiles, J. (1995). Plasticity and development. Evidence from children
with early occurring focal brain injury. In B. Julesz and I. Kovacs (Eds.), Maturational
windows and adult cortical plasticity. Reading, MA: Addison-Wesley.
Vroomen J, de Gelder B (2000). Sound enhances visual perception: Cross-modal
effects of auditory organization on visual perception. J Exp Psychol (in
Wallace, M. T., Wilkinson, L. K. & Stein, B. E (1996). J
Neurophysiol 76: 1246–1266
Weisstein, N., & Harris, C.S. (1980). Masking and unmasking of
distributed representations in the visual system. In C.S. Harris (Ed.), Visual
coding and adaptability (pp. 317-364). Hillsdale, NJ: Lawrence Erlbaum
Whitaker, D and McGraw, P.V.
Long-term visual experience recalibrates human orientation perception. Nature
Yeo. R. M., Yonebayashi, Y., & Allman, J. M. (1995). Perceptual
memory of cognitively defined contours: A rapid, robust and long-lasting form
of memory. In B. Julesz and I. Kovacs (Eds.), Maturational windows and adult
cortical pasticity. Reading, MA: Addison-Wesley.
Zacks, J. et al (2001). How does the brain parse activities in the world
into discrete perceptual events? Nature Neurosci 4, 651–655
Zatorre, R.J., Halpern, A.R., Perry, D.W., Meyer, E., & Evans, A.C.
(1996). Hearing in the mind's ear: A PET investigation of musical imagery and
perception. Journal of Cognitive Neuroscience, 8, 29-46.