Linking Brain Response and Behavior to Reveal Top...

Linking Brain Response and Behavior to Reveal Top-Down

(and Inside-Out) Influences on Processing in Face Perception

Heather A. Wild

Thomas A. Busey

Department of Psychology

Indiana University

Bloomington, IN 47405

Please send correspondence to:

Heather Wild ([email protected])orTom Busey ([email protected])

Contextual Influences on Face-Related ERPs 2

Abstract

In two electrophysiological experiments we investigated contextual influences on

face and word recognition. An event-related potential component previously identified

with face processing (the N170) was shown to be modulated by task differences. Subjects

viewed faces and words embedded in fixed visual noise, and produced a larger N170 to

noise-alone trials when they expected a face. In a second experiment we found a larger

N170 on noise-alone trials when observers thought they saw a face. The results

demonstrate that the neurons responsible for the N170 are affected by a wider range of

influences than previously thought. In addition, the size of the N170 is related to the

behavioral response to an otherwise ambiguous stimulus, even in the absence of face-like

features. The results point to the intriguing suggestion that the illusion of a face in an

ambiguous display may result from greater activity in the temporal lobe face region.


Converging evidence from a variety of sources demonstrates that humans (and

other primates) have a special facility for face recognition, perhaps supported by

specialized areas in the inferotemporal cortex ( Kanwisher, N., McDermott, J. & Chun,

M. M.,1997; Tanaka & Farah, 1993). Research on neural correlates of face processing

suggests that areas of the inferotemporal (IT) cortex respond selectively to faces and

other complex visual stimuli with which the observer has extensive experience and

expertise (Gauthier, Tarr, Anderson, Skudlarski, & Gore, 1999). Single-cell recording in

nonhuman primates also shows face selectivity in IT neurons (Perrett, Rolls, & Cann,

1979; Young & Yamane, 1992), which are at the end of a series of processing stages that

extend along a pathway down the temporal lobe from earlier visual areas. In humans,

there is evidence for slight right-hemisphere dominance (Watanabe, S. Kakigi, R.,

Koyama, S., & Kirino, E., 1999). In addition, prosopagnosic individuals show evidence

of brain lesions in these areas and several show right-hemispheric specialization (Eimer

& McCarthy, 1999; Farah, Rabinowitz, Quinn, & Liu, 2000).

While much of the work has addressed the nature of the visual information that

results in activity in area IT, relatively little research has focused on other sources of

influence. In the present work we address the nature of contextual influences that are

brought to bear by the perceiver during face and word recognition, and address the degree

to which these contextual influences affect activity that occurs within 150-200

milliseconds after stimulus onset.

Electrophysiological (EEG) studies demonstrate that when a face stimulus is

visually presented to observers during recording, a negative-going potential occurs

around 170 ms after stimulus onset (Bentin, 1998; Bentin, Allison, Puce, Perez, &


McCarthy, 1996; Olivares & Iglesias, 2000). This downward deflection (which need not

extend below zero) is known in the EEG/ERP literature as the N170. The N170 is largest

at recording sites T5 and T6, roughly corresponding to the left and right temporal lobe

respectively (Bentin et al., 1996). Intracranial EEG recordings in epileptic human

observers reveal a face-specific negative-going potential at 170-200 ms in IT and the

fusiform gyrus (Allison, Puce, Spencer, & McCarthy, 1999; McCarthy, Puce, Belger, &

Allison, 1999; Puce, Allison, & McCarthy, 1999). In addition, using a combination of

MEG, EEG and source localization (BESA), Watanabe et al. (1999) have localized the

N170 response to regions of the inferotemporal cortex, around the fusiform gyrus. Thus

the locus of the N170 component appears to derive from the neurons in the

inferotemporal cortex.

The presentation of virtually any face or face-like stimulus results in an N170

component in the ERP. This is regardless of sex, age, emotional expression, or pose of

the face (Allison et al., 1999; McCarthy et al., 1999; Puce et al., 1999). Inverted (upside-

down) faces also yield an N170, although the onset is slightly delayed and the negative

deflection is slightly stronger (Bentin et al., 1996). Parts of faces (i.e., features alone) and

cartoon and animal faces also yield an N170, although it is sometimes attenuated and the

results are not entirely consistent (Allison et al., 1999; Bentin et al., 1996). Stimuli which

elicit an attenuated or nonexistent N170 include other highly homogenous classes of

symmetric complex visual stimuli such as flowers, cars, or butterflies; nonface bodyparts

(e.g., hands; McCarthy et al., 1999); and pixelwise scrambled faces and various

sinusoidal gratings (Allison et al., 1999). Components in the range of 100-150 ms have

been shown to be modulated by spatial attention (Hillyard & Anillo-Vento, 1998) but


these studies seem to indicate that modulation of these components by non-spatial

features such color, motion or shape depends on spatial attention. Thus selecting a class

of features (such as those in faces or words) without first selecting a spatial location may

not be sufficient to modulate the N170.

Researchers have examined whether there are top-down influences other than

spatial attention on the N170 for faces and, until recently, have found none. There

appears to be no modulation of the N170 by task demands, such as whether the face is a

target stimulus or not (Cauquil, Edmonds, & Taylor, 2000), and no effect of familiarity of

the face (Bentin & Deouell, 2000). This suggests that the N170 indexes purely perceptual

or bottom-up processes. Additionally, fMRI studies reveal that face-specific brain areas

are active any time there is a face in a scene, regardless of whether the face is relevant to

the task at hand (Gauthier et al., 1999). Thus, the neural response of cells in IT appears to

arise from feed-forward perceptual processing of faces. In support of this, Bentin et al.

(1996) suggested that the N170 indexes an automatically activated neural face detection

mechanism.

However, a recent study by Bentin and colleagues (Bentin, Sagiv, Mecklinger,

Friederici, & von Cramon, 2002) has altered this view. Subjects were first shown pairs of

dots, plus signs, or other simple shapes. These failed to elicit a strong N170. The pairs of

dots were then place into a face context, where the dots became the eyes of a schematic

face. When the observers were again shown just the pairs of shapes, they reported

interpreting the shapes as eyes, and more importantly, the shapes and the complete faces

produced equivalent N170s. These results suggest that the N170 can be modulated by

contextual information.


Bentin et al. (2002) took advantage of the fact that pairs of dots can sometimes be

interpreted as eyes. In the present work we address whether the N170 can be modulated

in the absence of any face-like stimulus, even in the absence of any task demands or prior

experience with the stimuli. If so, this would re-define the response properties of the

neurons responsible for the N170. To accomplish this, we embedded faces and words in

visual noise, and varied the task or other factors.

The critical conditions derive from trials in which only noise is presented to the

subject. Our noise is not resampled on each trial, and thus we hold the physical stimulus

constant across the tasks for the noise-alone conditions. In Experiment 1 we ask whether

the subject produces a larger N170 to the noise alone trials when they are looking for

faces than when looking for words. In Experiment 2 we ask whether subjects produce a

larger N170 to the noise-alone trials when they thought they saw a face, compared to a

word. The results indicate that the N170 is not just the signature of a feed-forward face

detector, but is affected by contextual information even in the absence of face-like

features. Surprisingly, on noise-alone trials there appears to be a direct relation between

the size of the N170 and whether the observer reports a face or a word was presented.

Experiment 1

In Experiment 1 observers made face or word judgments to faces and words

embedded in noise. The trials were blocked by task. The critical question is whether

observers will make a larger N170 to the noise-alone trials when looking for faces than

when looking for words.

Methods

Participants


Nine observers, eight of which were right-handed, participated in the study. These

observers were research assistants from our lab and/or students at IU whose participation

comprised part of their labwork or coursework. All observers were na ve as to the

purpose of the study.

Apparatus and EEG recording parameters

The EEG was sampled at 1000 Hz and amplified by a factor of 20,000 (Grass

amps model P511K) and band-pass filtered at .1 - 100 Hz (notch at 60 Hz). Signals were

recorded from sites F3, F4, Cz, T5, and T6, with a nose reference and forehead ground;

all channels had below 5 kOhm impedance. Recording was done inside a Faraday cage.

Eyeblink trials were identified from channels F3 and F4 and removed from the analysis

with the help of blink calibration trials. Images were shown on a 21 inch (53.34 cm)

Macintosh grayscale monitor approximately 44 inches (112 cm) from participants. Data

were collected by a PowerMac 7100. These details were identical for Experiment 2.

Stimuli

The stimuli for both experiments appear in Figure 1. Face stimuli consisted of

frontal views of one male and one female face with neutral expressions, generated using

the PoserTM application (Metacreations). Faces subtended a visual angle of 2.1 x 2.8

degrees. Two low imagery words were chosen for the second task ( Honesty and

Trust ). Words subtended a visual angle of 1.1 x .37 degrees. All stimuli were

embedded in white noise (4.33 x 4.33 degrees of visual angle) that was fixed (i.e. not

resampled) on all trials. The faces and words were presented at three contrast levels

(high, low, and zero). The zero contrast condition contained just noise and therefore had

no correct answer. The identical stimuli were used in Experiment 2.


Procedure

Participants completed the face task in the first half of the experiment and the

word task in the second half. In the face task, observers made male/female judgments on

100 trials per contrast level that were presented in random order within the face block.

The word task involved trust/honesty judgments, also with 100 trials per contrast level.

Observers were told that there was a stimulus present on every trial, but that it might be

difficult to see because of low contrast levels. Stimuli were presented for 1000 ms. EEG

was recorded from 100 ms prior to stimulus onset to 1100 ms post-stimulus onset. The

subject responded after the stimulus disappeared.

Results and Discussion - Experiment 1

EEG signals were averaged across trials for each subject within condition, such

that there were six ERP traces (high, medium, and zero contrast for faces and for words).

As expected, the high-contrast face produced a much larger N170 than the high-contrast

word, and had a latency of about 170 ms. The critical trials of the experiment are those

where only noise was presented, because in these trials the physical stimulus is held

constant and only the subjects’ expectations vary (i.e. looking for a face or looking for a

word). The grand average ERPs collapsed across subjects for these conditions are

presented in Figure 2 (sites T5 and T6). Our central question is whether we see a larger

N170 in the noise-only trials when subjects expect a face than when they expect a word.

At both T6 and T5 there is a greater N170 when subjects are looking for a face. To assess

this difference statistically, we computed the average amplitude for each subject in the

time window from 140-200 ms for each condition. Across subjects, there was a

significantly greater negative potential for the face condition for T5 (two-tailed t(8) =


2.62, p= .031) and T6 (two-tailed t(8) = 2.35, p = .047). We also analyzed the P100 and

P300 components by averaging the amplitudes in the 80-130 ms and 260-340 ms

windows and found no significant differences.

We found a greater N170 on noise-alone trials where observers were expecting a

face rather than a word, despite the fact that the physical stimulus was identical on these

trials. These results demonstrate that top-down contextual factors can mediate the N170,

and are consistent with the results of Bentin (2002). The current results extend previous

results by demonstrating that the N170 can be modulated by contextual influences even

in the absence of face-like features.

Experiment 2

The contextual influences in Experiment 1 take the form of what might be thought

of as perceptual set. During a face block observers are looking for facial features, and

perhaps this involves attention to specific spatial frequency bands or features that fit the

response properties of the N170 neurons. This attentional tuning could occur well before

the start of a trial and be held constant throughout a block of trials.

To remove this pre-trial contextual information, in Experiment 2 we switched to a

mixed design. Subjects made a face/word discrimination on each trial, and again we

included the noise-only trials. The critical question is whether the N170 is larger on those

trials in which subject think they see a face in a noise-only display (relative to trials in

which they think they see a word). If so, this would relate the N170 activity directly to

the response and indicate how activity in this region might influence aspects of conscious

behavior such as perception and overt responding.

Methods


Participants

Ten right-handed observers participated in the study. These observers were

research assistants from our lab and/or students at IU whose participation comprised part

of their labwork or coursework. All observers were na ve as to the purpose of the study.

Procedure

The procedure was similar to that of Experiment 1, except that face and word

trials were intermixed and the task was to indicate whether a face or a word was

embedded in the noise. Observers responded via a joystick using a single finger, and were

asked to make speeded responses. This change was made to eliminate additional guessing

strategies not tied to the initial perceptual processing of the stimulus. The same stimuli

were presented as in Experiment 1 (high, low, or zero contrast faces and words embedded

in noise), and observers were told that there was a stimulus present on every trial, despite

the fact that one-third of the trials were noise-alone. Observers were also told that faces

and words appear equally often. There were a total of 720 trials.

Results and Discussion - Experiment 2

EEG signals were averaged across trials for each subject based on the stimulus

category for high or medium contrast words and faces, and the noise-only trials were

binned according to the subjects response (either ’face’ or ’word’). Again we found a large

N170 for the high contrast face, while the high contrast word showed a much later onset

and a reduced amplitude. There was a slight bias to say face such that observers made

this response on 62% of the noise-alone trials. As shown in Figure 3, on these noise-alone

trials, face responses are associated with a greater N170 than word responses in the

right temporal channel (T6) (two-tailed, t(9) = 2.74, p = .023), but not for the left


temporal channel (T5) (t(9) = 1.54, p = .157, ns). We also analyzed the P100 and P300 by

averaging the amplitudes in the 80-130 ms and 260-340 ms windows and found no

significant differences for either channel. Thus the differences in the ERPs between

face and word responses are confined to the right temporal lobe at about 170 ms after

stimulus onset.

The results of Experiment 2 demonstrate that the N170 is related to the response

given by subjects to an ambiguous stimulus (the noise-alone image). That the differences

were confined to the right temporal lobe at about 170 ms after stimulus onset puts strong

constraints on the nature of the processing that causes the differences in the EEG. Below

we discuss possible explanations for these differences at the N170 for the two responses.

General Discussion

In Experiment 1, we demonstrated that modulation of the EEG signal at 170 ms

can result from contextual influences in the absence of face-like features. Our noise-alone

display bears no resemblance to the perceptual stimuli that are typically reported in the

literature as generating an N170. First, there are no clearly identifiable face-like features.

Second, the display has a flat frequency spectrum, whereas faces have approximately a

1/f frequency spectrum. Third, pixelwise scrambled faces (which produces displays

similar to our white noise) do not yield an appreciable N170 (McCarthy et al., 1999).

Thus, we feel it is reasonable to conclude that we have excluded possible face-like

features from our noise-alone stimuli. The greater N170 on noise-alone trials in the face

block appears to be driven by expectations or differences in the nature of the perceptual

information acquired by the subject, rather than by bottom-up perceptual differences

since the physical stimulus was constant in the two blocks.


In Experiment 2 we found that observers show a greater N170 when they think

they see a face in the noise rather than a word, an effect which is localized to the right

temporal lobe. These results establish a link between the magnitude of the neural

response at 170 ms and the behavioral response (i.e., whether observers say they saw a

face). This is neither the result of bottom-up nor top-down influences, but rather

demonstrates what might be thought of as inside-out processing. Under this account,

the internal response of N170 neurons varies from trial to trial due to internal noise or

other stochastic processes. When faced with a noise-only trial that occurs in conjunction

with a greater activity level in the N170 neurons, the observer may experience the

illusion of the presence of a face and respond accordingly. In support of this hypothesis,

several studies have found that observers report face and face-like percepts following

intracranial stimulation of face-specific areas of the cortex (Puce et al., 1999; Vignal,

Chauvel, & Halgren, 2000). In our experiments this illusion may be quite faint, but

sufficient to bias the subject’s response on noise-alone trials.

Before accepting this candidate hypothesis, we must first rule out several other

plausible explanations for this effect. First, the activity at 170 ms occurs too early to

simply be a signature of the observer s response after it had been executed, since the

median reaction times were around 600 ms for both conditions. Thus while it is possible

(even likely) that the N170 neurons influence the decision, it is unlikely that the subject s

decision influences the electrophysiological response at 170 ms.

The inside-out account assumes that the decision process starts once the trial

begins. One candidate mechanism that would allow the process to start earlier would be

priming from the previous trial. We explored this possibility by examining whether the


presentation of a face on the previous trial resulted in a larger N170 on the current noise-

alone trials. As shown in the left panel of Figure 4, the size of the N170 to noise-alone

trials has only a slight dependence on whether a face or a word was presented on the

previous trial. Noise-alone trials preceded by a face produced a reduced N170, which

contradicts the priming hypothesis. This difference is significant (t(9) = 2.43, p = 0.038)

mainly due to differences that occur late in the window. However, as shown in the right

panel of Figure 4, this effect is due entirely to differences on trials in which observers

responded word to the noise-alone stimulus. For ’face’ responses to noise-alone trials,

there were no differences in the EEG depending on whether the prior trial had been a face

or a word (t(9) = .04, p=0.96). However, there was a slightly smaller N170 for word-

response noise-alone trials that were preceded by a face stimulus (t(9) = 3.24, p = .01),

which again contradicts the priming hypothesis. One possible explanation is negative

priming from the stimulus on the prior trial, but it is not clear why the effects of prior-

trial priming should be restricted to noise-alone trials in which the observer responded

word . In addition, this effect is only a small part of the large difference seen in Figure 3

(right panel). This can be observed in the right panel of figure 4 by collapsing the dark

lines together and the light lines together to recover the original effect in Figure 3. This

shows that the overall differences between the two responses are much larger than the

differences conditioned on a ’word’ response’. Thus we rule out the prior-trial priming

explanation as a major influence on our results in Experiment 21.

1 Of course, we could also look at whether the response on the previous trial is correlated with themagnitude of the N170 on the present trial. However, as observers had extremely high accuracy levels, theresponses and stimuli on previous trials were strongly correlated and thus the analysis would yield the sameconclusions.


A second possible explanation for the results of Experiment 2 is that observers

attend to face-like features or face-specific spatial frequency bands of the noise on some

trials, which provides a stronger input to the N170 neurons, leading to a larger N170 and

an overt face response. This explanation is of interest because it still ties the N170

activity to the behavioral response, although it doesn’t explain why subjects should decide

to look for a face on a particular trial. However, Gold, Bennett, & Sekuler (1998) have

shown that faces and words are processed by humans using the similar spatial frequency

filters despite the vastly different spatial frequency content. Thus attention to a particular

spatial frequency band by the observer in order to detect one type of stimulus may not

provide greater input to the N170 neurons. In addition, Puce et al. (1999) showed that

bandpass filtered faces, which include just high or just low spatial frequencies, give

equivalent N170 responses that are as strong as the N170 to the unfiltered face, and so

changing the spatial frequency content in the input to the N170 via selective attention to

different spatial frequency bands may not be sufficient to modulate the N170.

Having at least tentatively eliminated explanations based on prior-trial priming

and attention to different features in the noise, we are left with the intriguing possibility

that the behavioral response is directly related to the activity in the N170 neurons. That

is, when presented with an ambiguous stimulus, observers may have a tendency to think

they saw a face when the activity of the N170 neurons is higher.

The data from both experiments lead to the view that the processing of faces, as

indexed by the N170, is much more flexible and amenable to contextual influences than

has previously been reported in the literature. The N170 does not seem to simply reflect a

feedfoward face detector, but instead responds to the demands of the task and perhaps


internal influences. In Experiment 1, observers performing face or word tasks may tune

the behavior of the N170 neurons through top-down connections. In Experiment 2, the

differences may come from internal sources at the N170 neurons, but still influence

behavior. Thus we propose that, given no other information, internal activity may bias an

overt response, through processes we term inside-out influences. The fact that we can

link the activity in the N170 neurons to the behavioral response suggests that the output

of these neurons eventually becomes available to conscious awareness. The source of this

internal activity may be viewed as a form of internal noise that varies from trial to trial,

influencing the processing of perceptual input.

One way to investigate the nature of internal noise sources is to add external noise

to the stimulus, which grown recently as a method for measuring internal noise and

perceptual templates (Ahumada, 1987; Dosher & Lu, 1999; Gold, Bennett, & Sekuler,

1999a, 1999b; Gold, Murray, Bennett, & Sekuler, 2000; Skoczenski & Norcia, 1998; see

Pelli & Farell, 1999, for a review of methods). The current study used external noise

simply to create an ambiguous stimulus. However, the results point to a type of internal

noise in the face processing neurons that ultimately influences behavior, rather than a

noise source that simply limits performance. It seems likely that EEG recording may help

define the nature of the internal noise, and when used in conjunction with modeling, may

help tease apart current debates on the nature of internal noise (i.e., additive or

multiplicative noise; e.g. Dosher & Lu, 1999). By relying on the time course of the

signal, the nature of the internal noise at different stages of processing might be revealed.

We are currently investigating how EEG data can be used with resampled noise to

compute classification images (Gold et al., 2000). This is the EEG analog of the reverse


correlation technique in single-cell recording that has been used to map out the receptive

fields of single neurons (e.g. DeAngelis, Ohzawa & Freeman, 1995). The hope is that the

EEG signal will reveal, at a gross level, the response properties of the N170 neurons.

The strength of the current approach is that it holds the physical stimulus constant

in order to remove explanations based on different attributes of the stimuli. This allows

us to tie the response of the neurons in area IT to the behavioral response and reveal

evidence of non-perceptual influences. Similar techniques could be applied to other

domains such as spatial attention and object recognition to disambiguate bottom-up, top-

down and inside-out processes.


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Figure 1. Stimuli for experiments 1 and 2. From left to right: high- and low-contrast

female and male faces; noise alone; and low- and high-contrast words ( Honesty and

Trust ). Note that the noise is identical for all stimuli.

High ContrastFaces

High ContrastWords

Low ContrastWords

Low ContrastFaces

Noise Alone


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Figure 2. Experiment 1. Event-related potentials (ERPs) elicited at temporal lobe sites T5 (left panel, lefthemisphere) and T6 (right panel, right hemisphere). Solid lines indicate noise-alone trials where observers areexpecting a face; dashed lines indicate noise-alone trials where observers are expecting a word. The two asterisksindicate significant effects at the N170 component.


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Figure 3. Experiment 2. ERPs elicited at temporal lobe sites T5 (left panel, left hemisphere) and T6 (rightpanel, right hemisphere). Solid lines indicate noise-alone trials where observers thought they saw a face;dashed lines indicate noise-alone trials where observers thought they saw a word. The asterisk in the rightpanel indicate significant differences between the two responses at the N170 component.


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Figure 4. Data from Experiment 2, channel T6 (right hemisphere). ERP traces from noise-alone trialsconditioned on the stimulus presented on the prior trial (left panel) and on prior trial and response (rightpanel). Note that the time scale is different than in prior figures to emphasize effects at the N170. Theasterisk in the left panel indicates a significant difference between the two conditions at the N170, duemainly to the differences late in the averaging window.

Linking Brain Response and Behavior to Reveal Top...

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