Pupillometry a Window to the Preconscious

http://pps.sagepub.com/Science

Perspectives on Psychological

http://pps.sagepub.com/content/7/1/18The online version of this article can be found at:

DOI: 10.1177/1745691611427305 2012 7: 18Perspectives on Psychological Science

Bruno Laeng, Sylvain Sirois and Gustaf GredebckPupillometry: A Window to the Preconscious?

Published by:

http://www.sagepublications.com

On behalf of:

Association For Psychological Science

can be found at:Perspectives on Psychological ScienceAdditional services and information for

http://pps.sagepub.com/cgi/alertsEmail Alerts:

http://pps.sagepub.com/subscriptionsSubscriptions:

http://www.sagepub.com/journalsReprints.navReprints:

http://www.sagepub.com/journalsPermissions.navPermissions:

by guest on March 28, 2014pps.sagepub.comDownloaded from by guest on March 28, 2014pps.sagepub.comDownloaded from

Perspectives on Psychological Science7(1) 18 27 The Author(s) 2012Reprints and permission: sagepub.com/journalsPermissions.navDOI: 10.1177/1745691611427305http://pps.sagepub.com

The measurement of the diameter of the eyes pupils (in short, pupillometry) within psychology just celebrated 50 years. Researchers have firmly established that the pupil changes size not only in response to changes in ambient light (the pupillary light reflex), but also to significant nonvisual stimuli as well as thoughts and emotions (Goldwater, 1972; Loewenfeld, 1993). Although psychologists have made spo-radic attempts to measure changes in the diameter of the pupil prior to 1960 (e.g., Berrien & Huntington, 1943; Watson, 1916), a study by Hess and Polt (1960) represents the turning point for establishing the method within the psychological research community (Andreassi, 1995). Hesss study mea-sured pupillary sizes of male and female adults while they viewed photographic semi-nudes of adults of both sexes as well as pictures of babies. As one could predict, the pupils of both male and female observers dilated (of about 20% of the diameter compared to baseline) when they viewed images of half-naked members of the opposite sex, whereas only the female observers shows significant dilations to pictures of babies. A few years later, it became clear that pupillary responses do not only constitute a response to arousing or emotionally relevant stimuli (e.g., Aboyoun & Dabbs, 1998; Bernick, Kling, & Borowitz, 1971; Hamel, 1974; Hess, Seltzer, & Shlien, 1965; Peavler & McLaughlin, 1967), but could also express other fundamental cognitive mechanisms.

For example, increasing load on memory, by increasing the span of a string of digits to be remembered, positively corre-lated with pupillary size (Beatty & Kahneman, 1966). A few years earlier, Hess and Polt (1964) similarly demonstrated that difficulty of mental calculations (e.g., multiplication) corre-lated positively with the size of the pupil (see also Ahern & Beatty, 1979). In Kahnemans (1973) words, the eyes pupil seemed to provide a window on the intensive aspect of attention (i.e., its capacity, distinct from its selective aspect), an often overlooked attentional variable within the cognitive sciences. Similar suggestions have been brought for-ward more recently. Just and Carpenter (1993) described the pupillary response as an indicator of how intensely the pro-cessing system is operating.

Kahnemans (1973) account of the pupillary response as an index of load on attentional capacity is still useful, as many subsequent studies have clearly shown a relationship between pupillary dilation and executive load or working memory load (e.g., Ahern & Beatty, 1979; Chatham, Frank, & Munakata, 2009; Hyn, Tommola, & Alaja, 1995; Kahneman & Peavler,

Corresponding Author:Bruno Laeng, Department of Psychology, University of Oslo, 1094 Blindern, 0317 Oslo, Norway E-mail: [email protected]

Pupillometry: A Window to the Preconscious?

Bruno Laeng1, Sylvain Sirois2, and Gustaf Gredebck31Department of Psychology, University of Oslo, 2Universit du Qubec Trois-Rivires, and 3Uppsala University

Abstract

The measurement of pupil diameter in psychology (in short, pupillometry) has just celebrated 50 years. The method established itself after the appearance of three seminal studies (Hess & Polt, 1960, 1964; Kahneman & Beatty, 1966). Since then, the method has continued to play a significant role within the field, and pupillary responses have been successfully used to provide an estimate of the intensity of mental activity and of changes in mental states, particularly changes in the allocation of attention and the consolidation of perception. Remarkably, pupillary responses provide a continuous measure regardless of whether the participant is aware of such changes. More recently, research in neuroscience has revealed a tight correlation between the activity of the locus coeruleus (i.e., the hub of the noradrenergic system) and pupillary dilation. As we discuss in this short review, these neurophysiological findings provide new important insights to the meaning of pupillary responses for mental activity. Finally, given that pupillary responses can be easily measured in a noninvasive manner, occur from birth, and can occur in the absence of voluntary, conscious processes, they constitute a very promising tool for the study of preverbal (e.g., infants) or nonverbal participants (e.g., animals, neurological patients).

Keywords

attention, consciousness, development, infant, methodology, neuroscience, neuroscience, unconscious/automatic processing

by guest on March 28, 2014pps.sagepub.comDownloaded from

Pupillometry 19

1969; Karatekin, Couperous, & Marcus, 2004; Nuthmann & van der Meer, 2005; Piquado, Isaacowitz, & Wingfield, 2010; Stanners, Coulter, Sweet, & Murphy, 1979; Van Gerven, Paas, Van Merrinboer, & Schmidt, 2004; V et al., 2008) and inter-ference or competition between stimuli and/or responses (e.g., Laeng, rbo, Holmlund, & Miozzo, 2011; Moresi et al., 2008; Siegle, Ichikawa, & Steinhauer, 2008; Van der Meer et al., 2003). Figure 1, for example, illustrates how the pupillary response is clearly sensitive to the congruency effect of the classic Stroop color-naming task.

However, recent evidence from pupillometry studies within psychology and neuroscience indicates that the pupillary response might offer a wider window on cognition than previ-ously thought. Specifically, it may provide an index to pro-cesses that occur below the threshold of consciousness.

Through the Eye to the BrainPupillary measurements

The size of the pupil of the eye is determined by the tone of two muscles, the dilator and the constrictor; thus, a pupillary dilation can be the result of a stimulation of the dilator or an inhibition of the constrictor. In dim light or darkness, the pupil can enlarge to an average size of about 7 mm with a standard deviation (from this average) of about 0.9 mm (MacLachlan & Howland, 2002); in standard light conditions, its average size is about 3 mm (Wyatt, 1995). Thus, changes in illumination can provoke pupillary dilations of more than double its typical size (about 120%). Changes that are cognitively driven are

more modest and are rarely greater than 0.5 mm (Beatty & Lucero-Wagoner, 2000). Thus, the pupillary response to sex-ual stimuli, as originally measured by Hess and Polt (1960), approximated the maximal dilation (a 20% change) that can be elicited by psychologically relevant stimuli that are invariant in luminance.

Pupillary responses occur spontaneously and they are dif-ficult to control voluntarily. Specifically, a pupillary dilation may be voluntarily provoked only in an indirect manner by mentally imaging an object or event that would normally evoke a pupillary dilation (e.g., sexual imagery; Whipple, Ogden, & Komisaruk, 1992). However, it is impossible to sup-press a pupillary dilation at will, whether it is provoked by external stimuli or mental events (Loewenfeld, 1993). Pupil-lary dilations evoked by psychologically relevant stimuli occur as the result of a neural inhibitory mechanism on the parasympathetic oculomotor complex or EdingerWestphal nucleus by the noradrenergic systems locus coeruleus (LC; Wilhelm, Wilhelm, & Ldtke, 1999).

Norepinephrine and the LCThe LC is a subcortical brain structure that constitutes the nor-adrenergic systems hub to the whole brain (Aston-Jones & Cohen, 2005; Sara, 2009). The LC is found on each side of the rostral pons in the brainstem and gives rise to the sole source of the neuro-transmitter norepinephrine (NE) to the cortex, cerebellum, and hippocampus. The LC may be most known among clinical psychologists for its role in syndromes like clinical depression, panic disorder, and anxiety (e.g., Carter

200200

400 600 800 1,000 1,200 1,400 1,600 1,800 2,000ms

0.02

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

mm

CongruentIncongruentNon-color words

Fig. 1. Mean pupil diameters (in mm) for each distractor condition during the classic color-word Stroop interference task (from Laeng et al., 2011). Time 0 represents the onset of each stimulus, and pupil size was sampled every 20 ms. The colored vertical lines represent the point in time of each conditions mean reaction time. Pupillary responses clearly lag behind each explicit response (a key press indicating the color of the word), but they showed the same pattern of results across conditions (i.e., larger responses for incongruent combinations of pixel colors and color words than for the congruent combinations).


20 Laeng et al.

et al., 2010; Klimek et al., 1997). The LC is activated by stress and responds to it by increasing NE secretion through the hypothalamicpituitaryadrenal axis and by altering the activ-ity of prefrontal cortex. In addition, the LC is engaged during the process of memory retrieval (Sterpenich et al., 2006) and slow-wave sleep (Eschenko & Sara, 2008), suggesting a role of the LCNE system in the consolidation of memories. At the same time, the LC sends its densest innervations to brain areas known to be involved in selective attention processing (e.g., parietal cortex, pulvinar nucleus, superior colliculus; Foote & Morrison, 1987). One current hypothesis is that the noradren-ergic system, which originates in the LC, mediates the func-tional integration of the whole attentional brain system (Corbetta, Patel, & Shulman, 2008; Coull, Bchel, Friston, & Frith, 1999; Sara, 2009). Recently, Posner and Fan (2008) have distinguished between alerting, orienting, and executive networks of the brain. Within their model, the alerting network is innervated by the NE system and includes the LC, right frontal cortex, and regions of the parietal cortex. Within this view, NE plays a crucial role in energizing the cortical system and promoting adequate levels of activation for cognitive performance.

What is most relevant for the present discussion about the neurophysiology of pupillary response is that neuroscientists have noted a very tight link between the online pupillary response and the activation of the LC and NE system (Koss, 1986). The LC might be a key node within the neural circuitry that also controls the muscles of the iris (Samuels & Szabadi, 2008), so that activity within this system gets reflected in the dilation of the eyes pupil. The existence of such a relationship allows researchers to map changes in LC activation through pupil diameter, providing an externally observable response that reflects activity of specific subcortical loci (Koss, 1986). In addition, given that the LC is the key node of the noradren-ergic system, pupillary responses can also be used to monitor the activity of the NE system by simply observing relative changes in pupil diameter or, in a metaphor, by using the natu-ral pupillary resonance signal from the NE system. As such, the connection between pupil diameter, the LC, and the NE system allows researchers to measure pupil diameter in order to tap changes in attention.

The above assumption is based on robust findings from neuroscience that have established, by use of the single-cell recording technique in monkeys, that changes in pupillary diameter are tightly correlated to changes in activity in neu-rons of the LC (Rajkowski, Kubiak, & Aston-Jones, 1993; Rajkowski, Majczynski, Clayton, & Aston-Jones, 2004). Figure 2 illustrates the close direct relationship between the pupil diameter and baseline firing rate of LC neurons in the monkey.

In the present review, we suggest that pupillary responses can index changes in allocation of attention (a) when a con-scious state about a stimulus or event is still in the making (i.e., in a preconscious active state but unable to reach aware-ness without top-down feedback; as defined by a recent theory

of consciousness by Dehaene, Changeux, Naccache, Sackur, & Sergent, 2006), (b) when a conscious state remains incom-plete (e.g., due to masking), or (c) cannot be made explicit either via verbal or motor responses (e.g., in preverbal infants, animals, and in some neurological patients). The above find-ings should be viewed in the context of recent neurophysiolog-ical evidence about the function of a small structure of the brain: the LC.

Phasic and tonic activity in the LC. According to Aston-Jones and Cohen (2005), two different modes of LC activity correspond to different patterns of an animals behavior. In the phasic mode, LC cells exhibit activation when processing task-relevant stimuli, and this mode of function is consistently associated with high levels of task performance (Aston-Jones, Rajkowski, Kubiak, & Alexinsky, 1994; Bouret, Duvel, Onat, & Sara, 2003; Usher, Cohen, Servan-Schreiber, Rajkowski, & Aston-Jones, 1999). In the tonic mode, LC cells fail to respond phasically to task events, and the animals exhibit poor perfor-mance on tasks that require focused attention and show an increase in distractibility. However, the animal is more likely to detect novel stimuli in the tonic mode. This dissociation in functional modes points to two fundamental cognitive mecha-nisms: A focused or exploitation mode that adaptively adjusts attentional filtering to optimize performance during a specific task or event, and a diffuse or exploration mode that adaptively adjusts the scope of attention to optimize shifts of performance between tasks or events (see Table 1).

If LC tonic activity favors exploration and abandoning a current task for another, whereas LC phasic activity signals the occurrence of task-relevant events, then we would expect pupillometry studies to reveal the same relationship between tonic and phasic pupillary changes in humans during the same conditions. An ample variety of studies have consistently

0 2,000 4,000Time (s)

1.0

1.5

Constrict

Dilate

LC N

euro

n (H

z)P

upil

Dia

met

e r

Fig. 2. The above curve shows pupil diameters as taken by a remote eye-tracking camera while a monkey fixed gaze on a spot of light during a signal-detection task. The curve below displays the baseline firing rate of an LC neuron while it was recorded from an electrode simultaneously to the pupillary responses. The two measurements are shown phased-locked to one another (from Aston-Jones & Cohen, 2005).


Pupillometry 21

shown that processing task-relevant events is time locked to rapid (phasic) and dramatic pupillary dilations (Beatty, 1982; Kahneman & Peavler, 1969; Poock, 1973; Richer & Beatty, 1985; Simpson, 1969). For example, when participants are asked to report the presence of a visual target during rapid serial visual presentation, pupil dilation is significantly associ-ated with target detection, and its amplitude reflects the fre-quency of targets and the time of the detection (Privitera, Renninger, Carney, Klein, & Aguilar, 2008). Indeed, any stim-uli that have some relevance to the observer are likely to pro-voke a pupillary response in the form of dilation (e.g., Hess et al., 1965, Hess & Polt, 1966; Janisse, 1974; Kuchinke, Trapp, Jacobs, & Leder, 2009; Libby, Lacey, & Lacey, 1973; Partala & Surakka, 2003).

Tonic changes in pupillary diameter have been investigated less than have changes that are time locked to the presentation of specific stimuli (i.e., event-related stimuli), despite the rel-evance of the brains tonic activation in Posners (1992, 1993) neural model of attention. Nevertheless, several studies con-verge to a similar relationship between pupillary tonic response and task difficulty, mental effort, and the state of arousal or vigilance of the participants. Sustained processing yields an increase in the pupil tonic response (e.g., Siegle et al., 2008). As difficulty and/or arousal increases, performance gradually degrades and large increases in pupillary baseline are concom-itantly observed (Beatty, 1982; Granholm, Asarnow, Sarkin, & Dykes, 1996; Howells, Stein, & Russell, 2010; Lavie, 1979; Peavler, 1974; Verney, Granholm, & Marshall, 2004). Con-versely, when the tonic state is low, as in a person who is fatigued after sustained attention or is sleepy, the pupil begins to fluctuate considerably while its average diameter gradually decreases (Beatty, 1982; Karatekin, Marcus, & Couperous, 2007). Indeed, the pupillographic sleepiness test has been used as an objective alertness test in European sleep research and sleep medicine (Wilhelm, Widman, Durst, Heine, & Otto, 2009; Wilhelm, Wilhelm, Ldtke, Streicher, & Adler, 1998).

Thus, the existing models of LC function (Aston-Jones & Cohen, 2005; Yu & Dayan, 2005) predict changes in both baseline- and stimulus-related pupil diameter in tasks in which both the difficulty and reward values of the task are concur-rently manipulated. Specifically, the model of Aston-Jones and Cohen (2005) correctly predicted that, in a tone discrimi-nation task, human pupillary responses would reveal large

phasic dilation for each discrimination but that these dilations would decrease in amplitude as difficulty increased while baseline (tonic) pupil diameter increased and peaked at the time participants decided to abandon the task and reset dif-ficulty to a lower level. Yu and Dayan (2005) proposed a Bayesian model of LC function, according to which a change in the environment (or an unexpected uncertainty) leads to a revision of an organisms optimal inferences and such a pro-cess is modulated by NE release by the LC.

Current models of the attention network in the human brain. The fact that the LC plays a key role in both focusing attention and disengaging ongoing action/thought is, in itself, a good neurophysiological premise for using the pupil as a window to changes in states of consciousness (Bouret & Sara, 2005). Attention and consciousness are intimately related, although they have not the same function and may depend on different cerebral processes and structures (Koch & Tsuchiya, 2006).

The influential biased-competition model of attention (Desimone & Duncan, 1995) proposes that objects in a visual scene compete for access to working memory and that atten-tion is biased by top-down (volitional) signals that promote the selection of relevant objects. These top-down signals in work-ing memory interact with the salient bottom-up signals of objects in the visual scene, so that the most relevant objects are selected attentively and thus perceived while unimportant objects are confined to a negligible status (Bundesen, Habekost, & Kyllingsbk, 2005; Wolfe, 1994, 2006).

Recently, two attentional systems have been distinguished (Corbetta et al., 2008): a selection system centered on the dor-sal portions of the parietal and frontal cortex responsible for the selection of sensory information and responses (Vanden-berghe, Gitelman, Parrish, & Mesulam, 2001), and a detection system, centered on the ventral portions of the temporo-pari-etal and frontal cortex responsible for the detection of relevant events, particularly salient and unattended stimuli (Raizada & Poldrack, 2008). The latter, ventral detection system might be most relevant for the type of information that is picked up by pupillary changes as this network receives strong input from the LCNE system.

Specifically, the LC phasic signal has been conceptualized as an interrupt signal or as a network reset signal (Bouret & Sara, 2004; Dayan & Yu, 2006) that allows the network to detect a new target or event. Neuroimaging studies of healthy humans suggest a functional relationship between signals of the LC and activity in the ventral attention network (Corbetta et al., 2008), both in relation to attentional transitions (tonic signals) and target detection (phasic response). The LC has a latency to a stimulus of about 100150 ms, and the transmis-sion of its output to the cortex is of about 50100 ms, which would allow a highly synchronized LC activation of the ven-tral attentional network, which in turn would allow the dorsal network to switch to and consolidate ones perception into another more appropriate state (Yantis & Serences, 2003).

Table 1. Performance Level in Perceptual or Cognitive Tasks as Predicted From an Animals Engagement in Each of Two Fundamental Modes of Attention and by Two Fundamental Neuronal Activation Modes of the Locus Coeruleus

Modes of locus coeruleus activity

Modes of attention

Focused exploitation Diffuse exploration

Phasic High performance Poor performanceTonic Poor performance High performance


22 Laeng et al.

Indeed, a decrease in tonic LC activity is observed whenever subjects engage in a demanding task, reflecting a top-down filtering signal that restricts the attentional focus to a narrow range of relevant events that are contingent to a task or mind set. Conversely, the high tonic LC activity is hypothesized to correspond to an exploratory, broad sensitivity mode to either external or internal (mental) events.

The pupil as a marker of attentional shifts. Recent studies of conscious perception have capitalized on the fact that some visual stimuli can give rise to different, often incompatible, perceptions. Some of the first examples of such images were Jastrows duck-rabbit, the Rubins vase-faces, and the so-called Necker cube. These bistable images as well as over-lapping images seen in binocular rivalry (i.e., when two completely different images are presented simultaneously but separately to each eye) are characterized by a conscious per-ception that oscillates in time between two different interpreta-tions of the same image so that sustained stimulations can result in repeated and rapid shifts between one conscious image or the other (Tong, Nakayama, Vaughan, & Kanwisher, 1998). During changes in perception, nothing changes in the world or environmental input, so any change in perception must be attributed to an internal change of state of the brain that results in interpreting the same world-state as a different event.

What is most interesting is that monitoring pupillary responses can reveal the brains detection of such event bound-aries evoked by the bistable image of the Necker cube (Einhuser, Stout, Koch, & Carter, 2008). Specifically, Einhuser and colleagues (2008) asked their participants to report the time of perceptual switching by pressing a button. As shown in Figure 3, it was found that the pupil diameter significantly increased around the time of the perceptual

switch and that the period of significantly larger dilations from baseline occurred within the time range of () 244 ms before and (+) 1552 ms after the reported switch with maximal peak at (+) 602 ms. Because a percepts dominance duration (i.e., how long one of competing percepts lasts) can fluctuate considerably between conditions, participants, and even within a trial, Ein-huser and colleagues calculated a normalized measure of post-switch duration relative to the corresponding preswitch duration, so that Point 0 of Figure 3 corresponds to equal durations before and after switches. Figure 3 also illustrates how the rate of increase in pupil dilation was maximal around the time of the switch in awareness and started just before its report. Finally, the larger the pupillary dilation around the time of the change in perception, the more stable the subsequent perception.

As Einhuser et al. (2008) also point out, their results are highly consistent with the previously sketched account by Aston-Jones and Cohen (2005), in which the pupillary response indicates LCs activity and NE levels in the brain in modulating between exploitation (e.g., continue what you are doing) and exploration (e.g., disengage and choose between one of the alternative possibilities). Moreover, the physiolog-ical plausibility of such an account is also strengthened by the consideration that, in monkeys, the LC phasic response occurs about 100 ms after a relevant event (e.g., a target stimulus sig-naling a reward) and it takes an additional 6070 ms for the activity within the LC nucleus to reach frontal cortex and about 100 ms for it to reach the occipital cortex. Such a delay from the triggering event to NE release at a cortical site is then about 150200 msa time course that is well within the range required for NE to plausibly have an influence on the crucial cortical network before the manual report of the change in per-ception. Although additional studies will be necessary to clar-ify the extent to which the pupillary response correlates to perceptual dynamics (see Hup, Lamirel, & Lorenceau, 2009), the above evidence strongly suggests that pupillary responses could provide an easily observable signal of the moment in which one event becomes relevant and consolidates into awareness, whereas alternative events are discarded and then eventually consigned to a negligible status.

The Preconscious PupilStimuli presented at the visual threshold (i.e., barely percepti-ble) tend to provoke significant pupillary dilations when they are detected (Hakerem & Sutton, 1966). However, recent stud-ies with normal participants have also revealed that the pres-ence of subliminal reward cues can trigger pupillary dilations that are proportional to the cues value as well as the level of demands of a costbenefits, decision-making task (Bijleveld, Custers, & Aarts, 2009). A study of Laeng and Falkenberg (2007) showed that women maximally dilated their pupils when passively viewing photographs of their boyfriends dur-ing the ovulatory (fertile) stage of their cycle, despite these hormone-based changes in motivational state typically going unnoticed by these participants. It would then seem that

0.8

0

0.43 +30

Time to Report [s]

Pup

il D

iam

et. [

z]

n = 398

p < .014

Fig. 3. Pupil diameter during the perceptual rivalry task produced by observing the Necker cube shape and reporting each reversal at the time of its occurrence by pressing a switch button. The pupil diameter scores are normalized to z scores and aligned to time of reported switch; means and standard errors were pooled across all switches of all subjects. The bottom horizontal black line denotes a period significantly different from 0 (from Einhuser, Stout, Koch, & Carter, 2008).


Pupillometry 23

pupillary dilations could also reflect changes of motivational state that occur below the threshold of perceptibility.

Weiskrantz, Cowey, and Barbur (1999) pointed out that the pupillary response, being nonverbal, lends itself particularly well to the investigation of residual visual capacity in neuro-logical patients that these patients themselves may not be aware to have retained. Patients with damage to the visual cor-tex (V1) often show blindsight; they can correctly guess about stimuli that they do not see (Weiskrantz, 1990, 1998) because the stimuli appear within their area of blindness. For example, in patients who suffered localized brain damage to V1, it is still possible to measure a reliable constriction of the pupil to spatial gratings presented within the blind field (Weiskrantz, Cowey, & Le Mare, 1998). The occurrence of the phenomenon of blindsight is supposedly based on processing by alternative neural pathways that bypass V1. Weiskrantz et al. (1999) found that the pupillary constriction response could be due to particular visual properties of gratings appearing and disap-pearing suddenly within the blind field, regardless of whether the patients reported any awareness of them. They concluded that although the pupillary response indirectly indexes a pro-cess that signals defensive and alerting reactions to stimuli that move rapidly and appear suddenly (e.g., events of special importance or danger), awareness is clearly not a necessary accompaniment to the presence of such a response.

Most remarkably, another study with blindsight patients showed that emotional faces seen within the blind area could provoke appropriate emotional responses from the patients (Tamietto et al., 2009). Specifically, the patients showed a spontaneous tendency to synchronize their facial expressions (i.e., a phenomenon known as emotional contagion) to the subliminal facial expressions shown within their blind area. Moreover, the pupillary responses showed larger dilation to the arousing value of the invisible emotional expressions. Another study, this time with amnesic patients with damage to the hippocampus (Laeng et al., 2007), has shown a remarkable ability of patients to discriminate novel stimuli from old ones, as revealed by their pupillary dilations to the new stimuli, despite the severe explicit memory problem and the total absence of an explicit discrimination between novel and the previously attended stimuli.

A constructive manner to interpret the unusual dissociations shown by these neurological patients is that some brain areas, including the amygdala, can process the stimuli but, without the support of cortical processes underlying a top-down attentional amplification of the represented information as well as recurrent loops of activity or functional connectivity between multiple areas (Dehaene et al., 2006; Lamme, 2006; Tononi, Sporns, & Edelman, 1992), a consciously accessible percept cannot be established. Normally, the information processed by these brain structures would be in a potential state of becoming an object of awareness and, indeed, the role attributed to several subcortical structures, like the amygdala and LC, is precisely that of warn-ing and alerting the (primarily frontal) cortical areas to switch the course of current processing so as to give relevance to new

stimuli or events or objectives (Duncan & Barrett, 2007; Gompf et al., 2010; Laeng et al., 2011; Liddell et al., 2005; Sterpenich et al., 2006). If, as a result of neurological damage, the workings of these areas remain isolated or functionally disconnected, then necessarily their information will remain confined to a poten-tial state that cannot be completely accessed. In other words, information that would be normally in a preconscious status would, in these pathological conditions, remain unconscious although still capable of influencing behavior, decisions, and emotional responses.

Indeed, the term preconscious has recently reappeared within the psychological taxonomy (Dehaene et al., 2006; see also Kihlstrom, 1995). The term was originally used by Freud (1900) for potential contents of awareness; that is, knowledge or mem-ories that are not presently conscious but that are accessible in principle (Laplanche & Pontalis, 1973). In Dehaene and col-leaguess (2006) tripartite model of conscious, preconscious, and subliminal processing, the preconscious state is a tran-sient one in which information is potentially accessible, yet not accessed. Chapman, Oka, Bradshaw, Jacobson, and Donaldson (1999) already explicitly suggested that the cognitive aspects of the pupillary response are preconscious; that is, the pupil can indicate the presence of processing that takes place before con-scious perception and that may be necessary for phenomenal awareness (cf. Block, 2005).

Developmental PupillometryStudying developmental populations most often require unique research paradigms that are not dependent on language or complex behavioral responses. For infant studies, this often means measuring the change in overall looking time from one stimulus set to another (habituation) or infants preference for one stimulus over another (preferential looking). For a discus-sion about the limitations of these measures, see Aslin (2007). For infant researchers, the analysis of pupillary responses allows novel questions about attentional states and precon-scious processes that are either time locked (phasic) or con-tinuous (tonic) over longer periods of time. To date, some initial studies have been carried out, suggesting that pupillary responses might be a robust and sensitive measure well suited for preverbal populations.

Early studies on infants (Fitzgerald, 1968; Fitzgerald, Lintz, Brackbill, & Adams, 1967; see Goldwater, 1972) observed greater pupillary dilation to pictures of faces than to geometric shapes, which is reminiscent of the early study by Fantz, Ordy, and Udelf (1962) on preferential looking of neonates on faces. Fitzgerald (1968) also found that the picture of the babys mother provoked greater pupillary dilation than did a picture of a stranger. However, the method used involved infrared film running at 2Hz and measuring by the diameter of the pupil by hand on a projection screen for each frame. This was tedious, expensive, and provided coarse data, which is possi-bly why (to the best of our knowledge) there was a 30-year gap before pupillometry was used again in infancy research.


24 Laeng et al.

Following this intermission, it has been demonstrated that pupillary responses differ as a function of age and of the spa-tial properties of grating stimuli in infants between 1 and 3 months of age (Cocker & Moseley, 1996). The amplitude and latency of light adaptation responses also decrease with increased postgestational age in prematurely born infants (Cocker, Fielder, Moseley, & Edwards, 2005).

In recent years, researchers have begun to revisit the con-nection between phasic pupillary responses and psychological processes that goes beyond vision. Jackson and Sirois (2009) demonstrated that 8-month-old infants react with larger pupil dilations after having observed a physically impossible event (one train entering a tunnel and another train exiting the same tunnel) relative to a more conventional physical event (the same train entered and exited the tunnel). Although pupil diameter proved a much finer discriminant variable relative to the traditional looking time measure, Jackson and Sirois (2009) found no correlation between look duration and peak pupil diameter. This finding invites further investigation given the important methodological implications it may have for the field. At the same time, Gredebck and Melinder (2010) used pupil dilation to assess infants reactions to violations of nor-mal social interactions. In this case, both 6- and 12-month-old infants dilated their pupils more after having observed irratio-nal than rational feeding actions (for recent studies with older children, see Anderson, Colombo, & Shaddy, 2006; Chatham et al., 2009; Falck-Ytter, 2008; Piquado et al., 2010).

These differential pupillary responses to surprising physi-cal events (Jackson & Sirois, 2009) and irrational social inter-actions (Gredebck & Melinder, 2010) might be related to arousal and increased cognitive load. This article provides three additional speculations that provide a plausible descrip-tion of the underlying mechanisms. First of all, the connection between arousal and/or cognitive load on one hand and pupil dilations on the other appeared to be mediated by alterations in the intensity of the attentional processing system (Ahern & Beatty, 1979; Just & Carpenter, 1993; Kahneman, 1973). Sec-ond, the phasic nature of infants reactions suggests that this alternation is primarily related to focused attention. Third, based on the adult and animal data reviewed above, it is fair to assume that reactions are preconscious and mediated by acti-vation within the LC and a surge of NE to the cortex.

ConclusionsOur goal in this article is to encourage researchers in several and often separate fields to benefit from the use of pupillom-etry. First of all, it is a relatively inexpensive method com-pared to several other physiological methods (EEG, fMRI, MEG) and it is completely noninvasive. An added advantage is that pupillometry is usually obtained by use of an eye tracker, and therefore it is often coupled to the acquisition of other continuous measurements of ocular data like eye fixa-tions and saccades, which can be phase locked to the unfolding of cognitive processes. Thus, eye movements and pupillary

responses share the benefit of providing clues about the real-time structuring of cognitive processing (cf. Richardson, Dale, & Spivey, 2007; Spivey, 2007). In fact, pupil recording can occur without any disruption of behavioral tasks and, as a non-invasive measure, it does not require overt responses and can be obtainable even without participant knowledge. Moreover, researchers can also profit from the sensitivity of pupil varia-tions to representations or responses that are only partially activated and that may never pass the threshold for eliciting overt behavior or conscious appraisal (Bijleveld et al., 2009; Laeng et al., 2007). One potential application of pupillometry could involve subjects that cannot normally understand instructions or provide controlled, verbal responses (e.g., aphasic patients, patients with locked-in syndrome).

However, the greatest promise of pupillometry may lie in its ability to reveal online processes that occur in experimental subjects who are either preverbal (i.e., infants; Gredebck & Melinder, 2010; Jackson & Sirois, 2009) or simply lack lan-guage (e.g., animals; Iriki, Tanaka, & Iwamura, 1996). We believe that a combination of the method with recent advances in infancy research allow us to start asking serious questions about consciousness early in ontology, and it may open an entire new frontier of research within developmental cognitive science and comparative psychology.

Declaration of Conflicting Interests

The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article.

Funding

This article was funded by Grants VR-2009-1348 and VR-2011-1528 from the Swedish Research Council.

References

Aboyoun, D. C., & Dabbs, J. M. (1998). The Hess pupil dilation findings: Sex or novelty? Social Behavior and Personality, 26, 415420.

Ahern, S., & Beatty, J. (1979). Pupillary responses during informa-tion processing vary with scholastic aptitude test scores. Science, 205, 12891292.

Anderson, C. J., Colombo, J., & Shaddy, D. (2006). Visual scanning and pupillary responses in young children with autism spectrum disorder. Journal of Clinical and Experimental Neuropsychology, 28, 12381256.

Andreassi, J. L. (1995). Psychophysiology: Human behavior and physiological response (3rd ed.). Hillsdale, NJ: Erlbaum.

Aslin, R. N. (2007). Whats in a look? Developmental Science, 10, 4853.

Aston-Jones, G., & Cohen, J. (2005). An integrative theory of locus coeruleus-norepinephrine function: Adaptive gain and optimal performance. Annual Review of Neuroscience, 28, 403450.

Aston-Jones, G., Rajkowski, J., Kubiak, P., & Alexinsky, T. (1994). Locus coeruleus neurons in monkey are selectively activated by attended cues in vigilance tasks. Journal of Neuroscience, 14, 44674480.


Pupillometry 25

Beatty, J. (1982). Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychological Bulletin, 91, 276292.

Beatty, J., & Kahneman, D. (1966). Pupillary changes in two memory tasks. Psychonomic Science, 5, 371372.

Beatty, J., & Lucero-Wagoner, B. (2000). The pupillary system. In J. T. Cacioppo, L. G. Tassinary, & G. Berntson (Eds.), Handbook of psychophysiology (pp. 142162). Cambridge, MA: Cambridge University Press.

Bernick, N., Kling, A., & Borowitz, G. (1971). Physiological differ-entiation of sexual arousal and anxiety. Psychosomatic Medicine, 33, 341352.

Berrien, F. K., & Huntington, G. H. (1943). An exploratory study of pupillary responses during deception. Journal of Experimental Psychology, 32, 443449.

Bijleveld, E., Custers, R., & Aarts, H. (2009). The unconscious eye opener: Pupil dilation reveals strategic recruitment of resources upon presentation of subliminal reward cues. Psychological Sci-ence, 20, 13131315.

Block, N. (2005). Two neural correlates of consciousness. Trends in Cognitive Sciences, 9, 4652.

Bouret, S., Duvel, A., Onat, S., & Sara, S. J. (2003). Phasic activation of locus coeruleus neurons by the central nucleus of the amyg-dala. Journal of Neuroscience, 23, 34913497.

Bouret, S., & Sara, S. J. (2004). Reward expectation, orientation of attention and locus coeruleus medial frontal cortex inter-play during learning. European Journal of Neuroscience, 20, 791802.

Bouret, S., & Sara, S. J. (2005). Network reset: A simplified over-arching theory of locus coeruleus noradrenaline function. Trends in Neuroscience, 28, 574582.

Bundesen, C., Habekost, T., & Kyllingsbk, S. (2005). A neural the-ory of visual attention. Bridging cognition and neurophysiology. Psychological Review, 112, 291328.

Carter, M. E., Yizhar, O., Chikahisa, S., Nguyen, H., Adamantidis, A., Nishino, S., . . . de Lecea, L. (2010). Tuning arousal with optogenetic modulation of locus coeruleus neurons. Nature Neu-roscience, 13, 15261533.

Chapman, C. R., Oka, S., Bradshaw, D. H., Jacobson, R. C., & Donaldson, G. W. (1999). Phasic pupil dilation response to noxious stimulation in normal volunteers: Relationship to brain evoked potentials and pain report. Psychophysiology, 36, 4452.

Chatham, C. H., Frank, M. J., & Munakata, Y. (2009). Pupillometric and behavioral markers of a development shift in the temporal dynamics of cognitive control. Proceedings of the National Acad-emy of Sciences, USA, 106, 55295533.

Cocker, K. D., Fielder, A. R., Moseley, M. J., & Edwards, A. D. (2005). Measurements of pupillary responses to light in term and preterm infants. Neuro-Ophthalmology, 29, 95101.

Cocker, K. D., & Moseley, M. J. (1996). Development of pupillary responses to grating stimuli. Ophthalmic Physiology and Optics, 16, 6467.

Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system of the human brain: From environment to theory of mind. Neuron, 58, 306324.

Coull, J. T., Bchel, C., Friston, K. J., & Frith, C. D. (1999). Norad-renergically mediated plasticity in a human attentional neuronal network. NeuroImage, 10, 705715.

Dayan, P., & Yu, A. J. (2006). Phasic norepinephrine: A neural inter-rupt signal for unexpected events. Network, 17, 335350.

Dehaene, S., Changeux, J.-P., Naccache, L., Sackur, J., & Sergent, C. (2006). Conscious, preconscious, and subliminal processing: A testable taxonomy. Trends in Cognitive Sciences, 10, 204211.

Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193222.

Duncan, S., & Barrett, L. F. (2007). The role of the amygdala in visual awareness. Trends in Cognitive Sciences, 11, 190192.

Einhuser, W., Stout, J., Koch, C., & Carter, O. (2008). Pupil dilation reflects perceptual selection and predicts subsequent stability in perceptual rivalry. Proceedings of the National Academy of Sci-ences, USA, 105, 17041709.

Eschenko, O., & Sara, S. J. (2008). Learning-dependent, transient increase of activity in noradrenergic neurons of locus coeruleus during slow wave sleep in the rat: Brain stem-cortex interplay for memory consolidation? Cerebral Cortex, 18, 25962603.

Falck-Ytter, T. (2008). Face inversion effects in autism: A com-bined looking time and pupillometric study. Autism Research, 1, 297306.

Fantz, R. L., Ordy, J. M., & Udelf, M. S. (1962). Maturation of pat-tern vision in infants during the first six months. Journal of Com-parative and Physiological Psychology, 55, 907917.

Fitzgerald, H. E. (1968). Autonomic pupillary reflex activity dur-ing early infancy and its relation to social and nonsocial visual stimuli. Journal of Experimental Child Psychology, 6, 470482.

Fitzgerald, H. E., Lintz, L. M., Brackbill, Y., & Adams, G. (1967). Time perception and conditioning an autonomic response in human infants. Perceptual and Motor Skills, 24, 479486.

Foote, S. L., & Morrison, J. H. (1987). Extrathalamic modulation of cortical function. Annual Review of Neuroscience, 10, 6795.

Freud, S. (1900). The interpretation of dreams. New York, NY: Mac-millan.

Goldwater, B. C. (1972). Psychological significance of pupillary movements. Psychological Bulletin, 77, 340355.

Gompf, H. S., Mathai, C., Fuller, P. M., Wood, D., Pedersen, N. P. A., Saper, C. B., & Lu, J. (2010). Locus coeruleus and anterior cingu-late cortex sustain wakefulness in a novel environment. Journal of Neuroscience, 30, 1454314551.

Granholm, E., Asarnow, R. F., Sarkin, A. J., & Dykes, K. L. (1996). Pupillary responses index cognitive resource limitations. Psycho-physiology, 33, 457461.

Gredebck, G., & Melinder, A. M. D. (2010). Infants understanding of everyday social interactions: A dual process account. Cogni-tion, 114, 197206.

Hakerem, G., & Sutton, S. (1966). Pupillary response at visual threshold. Nature, 212, 485486.

Hamel, R. F. (1974). Female subjective and pupillary reactions to nude male and female figures. Journal of Psychology, 87, 171175.

Hess, E. H., & Polt, J. M. (1960). Pupil size as related to interest value of visual stimuli. Science, 132, 349350.


26 Laeng et al.

Hess, E. H., & Polt, J. M. (1964). Pupil size in relation to mental activity during simple problem solving. Science, 140, 11901192.

Hess, E. H., & Polt, J. M. (1966). Changes in pupil size as a measure of taste difference. Perceptual and Motor Skills, 23, 451455.

Hess, E. H., Seltzer, A. L., & Shlien, J. M. (1965). Pupil responses of hetero- and homosexual males to pictures of men and women: A pilot study. Journal of Abnormal Psychology, 70, 165168.

Howells, F. M., Stein, D. J., & Russell, V. A. (2010). Perceived men-tal effort correlates with changes in tonic arousal during atten-tional tasks. Behavioral and Brain Functions, 6, 3954.

Hup, J.-M., Lamirel, C., & Lorenceau, J. (2009). Pupil dynamics during bistable motion perception. Journal of Vision, 9, 119.

Hyn, J., Tommola, J., & Alaja, A.-M. (1995). Pupil dilation as a measure of processing load in simultaneous interpretation and other language tasks. Quarterly Journal of Experimental Psy-chology, 48A, 598612.

Iriki, A., Tanaka, M., & Iwamura, Y. (1996). Attention-induced neu-ronal activity in the monkey somatosensory cortex revealed by pupillometrics. Neuroscience Research, 25, 173181.

Jackson, I., & Sirois, S. (2009). Infant cognition: Going full factorial with pupil dilation. Developmental Science, 12, 670679.

Janisse, M. P. (1974). Pupil size, affect and exposure frequency. Social Behavior and Personality, 2, 125146.

Just, M. A., & Carpenter, P. A. (1993). The intensity dimension of thought: Pupillometric indices of sentence processing. Canadian Journal of Experimental Psychology, 47, 310339.

Kahneman, D. (1973). Attention and effort. Engelwood Cliffs, NJ: Prentice Hall.

Kahneman, D., & Beatty, J. (1966). Pupil diameter and load on mem-ory. Science, 154, 15831585.

Kahneman, D., & Peavler, W. S. (1969). Incentive effects and pupil-lary changes in association learning. Journal of Experimental Psychology, 79, 312318.

Karatekin, C., Couperous, J. W., & Marcus, D. J. (2004). Attention allo-cation in the dual-task paradigm as measured through behavioural and psychophysiological responses. Psychophysiology, 41, 111.

Karatekin, C., Marcus, D. J., & Couperous, J. W. (2007). Regulations of cognitive resources during sustained attention and working mem-ory in 10-year-olds and adults. Psychophysiology, 44, 128144.

Kihlstrom, J. F. (1995). The rediscovery of the unconscious. In H. Morowitz & J. L. Singer (Eds.), The mind, the brain, and complex adaptive systems (pp. 123143). Reading, MA: Addison-Wesley Publishing.

Klimek, V., Stockmeier, C., Overholser, J., Meltzer, H. Y., Kalka, S., Dilley, G., & Ordway, G. A. (1997). Reduced levels of norepi-nephrine transporters in the locus coeruleus in major depression. Journal of Neuroscience, 17, 84518458.

Koch, C., & Tsuchiya, N. (2006). Attention and consciousness: Two distinct brain processes. Trends in Cognitive Sciences, 11, 1622.

Koss, M. (1986). Pupillary dilation as an index of central nervous system 2-adrenoceptor activation. Journal of Pharmacology Methods, 15, 119.

Kuchinke, L., Trapp, S., Jacobs, A. M., & Leder, H. (2009). Pupil-lary responses in art appreciation: Effects of aesthetic emotions. Psychology of Aesthetics, Creativity, and the Arts, 3, 156163.

Laeng, B., & Falkenberg, L. (2007). Womens pupillary responses to sexually significant others during the hormonal cycle. Hormones and Behavior, 52, 520530.

Laeng, B., rbo, M., Holmlund, T., & Miozzo, M. (2011). Pupillary Stroop effects. Cognitive Processing, 12, 1321.

Laeng, B., Waterloo, K., Johnsen, S. H., Bakke, S. J., Lg, T., Simon-sen, S. S., & Hgst, J. (2007). The eyes remember it: Oculog-raphy and pupillometry during recollection in three amnesic patients. Journal of Cognitive Neuroscience, 19, 18881904.

Lamme, V. A. F. (2006). Towards a true neural stance on conscious-ness. Trends in Cognitive Sciences, 10, 494501.

Laplanche, J., & Pontalis, J.-B. (1973). The language of psychoanaly-sis. London, England: Karnac.

Lavie, P. (1979). Ultradian rhythms in alertness: A pupillometric study. Biological Psychology, 9, 4962.

Libby, W. L., Lacey, B. C., & Lacey, J. I. (1973). Pupillary and cardiac activity during visual attention. Psychophysiology, 10, 270294.

Liddell, B. J., Brown, K. J., Kemp, A. H., Barton, M. J., Das, P., Peduto, A., . . . Williams, L. M. (2005). A direct brainstem-amyg-dala-cortical alarm system for subliminal signals of fear. Neu-roImage, 24, 235243.

Loewenfeld, I. (1993). The pupil: Anatomy, physiology, and clinical applications. Detroit, MI: Wayne State University Press.

MacLachlan, C., & Howland, H. C. (2002). Normal values and stan-dard deviations for pupil diameter and interpupillary distance in subjects aged 1 month to 19 years. Ophthalmic & Physiological Optics, 22, 175182.

Moresi, S., Adam, J. J., Rijken, J., Van Gerven, P. W. M., Kuipers, H., & Jolles, J. (2008). Pupil dilation in response preparation. Inter-national Journal of Psychophysiology, 67, 124130.

Nuthmann, A., & van der Meer, E. (2005). Times arrow and the pupillary response. Psychophysiology, 42, 306317.

Partala, T., & Surakka, V. (2003). Pupil size variation as an indication of affective processing. International Journal of Human-Computer Studies, 59, 185198.

Peavler, W. S. (1974). Pupil size, information overload, and perfor-mance differences. Psychophysiology, 11, 559566.

Peavler, W. S., & McLaughlin, J. P. (1967). The question of stimulus content and pupil size. Psychonomic Science, 8, 505506.

Piquado, T., Isaacowitz, D., & Wingfield, A. (2010). Pupillometry as a measure of cognitive effort in younger and older adults. Psy-chophysiology, 47, 110.

Poock, G. K. (1973). Information processing vs. pupil diameter. Per-ception and Motor Skills, 31, 587593.

Posner, M. I. (1992). Attention as a cognitive and neural system. Cur-rent Directions in Psychological Science, 1, 1114.

Posner, M. I. (1993). Interaction of arousal and selection in the pos-terior attention network. In A. Baddeley & L. Weiskrantz (Eds.), Attention: selection, awareness and control: A tribute to Donald Broadbent (pp. 390405). New York, NY: Oxford University Press.

Posner, M. I., & Fan, J. (2008). Attention as an organ system. In J. R. Pomerantz (Ed.), Topics in integrative neuroscience: From cells to cognition (1st ed., pp. 3161). Cambridge, UK: Cambridge University Press.


Pupillometry 27

Privitera, C. M., Renninger, L. W., Carney, T., Klein, S., & Aguilar, M. (2008). The pupil dilation response to visual detection. Human Vision and Electronic Imaging XIII. In B. E. Rogowitz & T. N. Pappas (Eds.), Proceedings of SPIE-IS&T Electronic Imaging (SPIE, Vol. 6806, pp. 68060T-168060T-11). San Jose, CA: SPIE.

Raizada, R. D. S., & Poldrack, R. A. (2008). Challenge-driven atten-tion: Interacting frontal and brainstem systems. Frontiers in Human Neuroscience, 1, 18.

Rajkowski, J., Kubiak, P., & Aston-Jones, G. (1993). Correlations between locus coeruleus (LC) neural activity, pupil diameter and behavior in monkey support a role of LC in attention. Society of Neuroscience Abstracts, 19, 974.

Rajkowski, J., Majczynski, H., Clayton, E., & Aston-Jones, G. (2004). Activation of monkey locus coeruleus neurons varies with difficulty and performance in a target detection task. Journal of Neurophysiology, 92, 361371.

Richardson, D. C., Dale, R., & Spivey, M. J. (2007). Eye movements in language and cognition: A brief introduction. In M. Gonzalez- Marquez, I. Mittelberg, S. Coulson, & M. J. Spivey (Eds.), Meth-ods in cognitive linguistics (pp. 323344). Amsterdam, Nether-lands: John Benjamins.

Richer, F., & Beatty, J. (1985). Pupillary dilations in movement prep-aration and execution. Psychophysiology, 22, 204207.

Samuels, E. R., & Szabadi, E. (2008). Functional neuroanatomy of the noradrenergic locus coeruleus: Its role in the regulation of arousal and autonomic function Part I: Principles of functional organisation. Current Neuropharmacology, 6, 119.

Sara, S. (2009). The locus coeruleus and noradrenergic modulation of cognition. Nature Reviews: Neuroscience, 10, 211223.

Siegle, C. J., Ichikawa, N., & Steinhauer, S. (2008). Blink before and after you think: Blinks occur prior to and following cognitive load indexed by pupillary responses. Psychophysiology, 45, 679687.

Simpson, H. M. (1969). Effects of a task-relevant response on pupil size. Psychophysiology, 6, 115121.

Spivey, M. (2007). The continuity of mind. Oxford, UK: Oxford Uni-versity Press.

Stanners, R. F., Coulter, M., Sweet, A. W., & Murphy, P. (1979). The pupillary response as an indicator of arousal and cognition. Moti-vation and Emotion, 3, 319339.

Sterpenich, V., DArgembau, A., Desseilles, M., Balteau, E., Albouy, G., Vandewalle, G., . . . Maquet, P. (2006). The locus ceruleus is involved in the successful retrieval of emotional memories in humans. Journal of Neuroscience, 26, 74167423.

Tamietto, M., Castelli, L., Vighetti, S., Perozzo, P., Geminiani, G., Weiskrantz, L., & de Gelder, B. (2009). Unseen facial and bodily expressions trigger fast emotional reactions. Proceedings of the National Academy of Sciences, USA, 106, 1766117666.

Tong, F., Nakayama, K., Vaughan, J. T., & Kanwisher, N. (1998). Binocular rivalry and visual awareness in human extrastriate cor-tex. Neuron, 21, 753759.

Tononi, G., Sporns, O., & Edelman, G. M. (1992). Reentry and the prob-lem of integrating multiple cortical areas: Simulation of dynamic integration in the visual system. Cerebral Cortex, 2, 310335.

Usher, M., Cohen, J. D., Servan-Schreiber, D., Rajkowski, J., & Aston-Jones, G. (1999). The role of locus coeruleus in the regula-tion of cognitive performance. Science, 283, 549554.

Vandenberghe, R., Gitelman, D. R., Parrish, T. B., & Mesulam, M. M. (2001). Functional specificity of superior parietal media-tion of spatial shifting. NeuroImage, 14, 661673.

Van der Meer, E., Beyer, R., Horn, J., Foth, M., Bornemann, B., Ries, J., . . . Wartenburger, I. (2003). Resource allocation and fluid intelli-gence: Insights from pupillometry. Psychophysiology, 47, 158169.

Van Gerven, P. W. M., Paas, F., Van Merrinboer, J. J. G., & Schmidt, H. G. (2004). Memory load and the cognitive pupillary response in aging. Psychophysiology, 41, 167174.

Verney, S. P., Granholm, E., & Marshall, S. P. (2004). Pupillary responses on the visual backward masking task reflect general cognitive abil-ity. International Journal of Psychophysiology, 52, 2336.

V, M. L. H., Jacobs, A. M., Kuchinke, L., Hofmann, M., Conrad, M., Schacht, A., & Hutzler, F. (2008). The coupling of emotion and cognition in the eye: Introducing the pupil old/new effect. Psychophysiology, 44, 130140.

Watson, J. B. (1916). The place of the conditioned-reflex in psychol-ogy. Psychological Review, 23, 89116.

Weiskrantz, L. (1990). Outlooks for blindsight: Explicit methodolo-gies for implicit processes. The Ferrier Lecture. Proceedings of the Royal Society Series B. London, 239, 247278.

Weiskrantz, L. (1998). Pupillary responses with and without aware-ness in blindsight. Consciousness and Cognition, 7, 324326.

Weiskrantz, L., Cowey, A., & Barbur, J. L. (1999). Differential pupil-lary constriction and awareness in the absence of striate cortex. Brain, 122, 15331538.

Weiskrantz, L., Cowey, A., & Le Mare, C. (1998). Learning from the pupil: A spatial visual channel in the absence of V1 in monkey and human. Brain, 121, 10651072.

Whipple, B., Ogden, G., & Komisaruk, B. R. (1992). Physiological correlates of imagery-induced orgasm in women. Archives of Sexual Behavior, 21, 121133.

Wilhelm, B., Widman, A., Durst, W., Heine, C., & Otto, G. (2009). Objective and quantitative analysis of daytime sleepiness in phy-sicians after duties. International Journal of Psychophysiology, 72, 307313.

Wilhelm, B., Wilhelm, H., & Ldtke, H. (1999). Pupillography: Princi-ples and applications in basic and clinical research. In J. Kuhlmann & M. Bttcher (Eds.), Pupillography: Principles, methods and applications (pp. 111). Mnchen, Germany: Zuckschwerdt Verlag.

Wilhelm, B., Wilhelm, H., Ldtke, H., Streicher, P., & Adler, M. (1998). Pupillographic assessment of sleepiness in sleep-deprived healthy subjects. Sleep, 21, 258265.

Wolfe, J. M. (1994). Guided search 2.0: A revised model of visual search. Psychonomic Bulletin & Review, 1, 202238.

Wolfe, J. M. (2006). Guided Search 4.0: Current progress with a model of visual search. In W. Grey (Ed.), Integrated models of cognitive systems (pp. 99119). New York, NY: Oxford Univer-sity Press.

Wyatt, H. J. (1995). The form of the human pupil. Vision Research, 35, 20212036.

Yantis, S., & Serences, J. T. (2003). Cortical mechanisms of space-based and object-based attentional control. Current Opinion in Neurobiology, 13, 187193.

Yu, A. J., & Dayan, P. (2005). Uncertainty, neuromodulation, and attention. Neuron, 46, 681692.


Documents

Pupillometry a Window to the Preconscious